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VOL 21 | NO 10

October 2010Vol. 21, Number 10gpsworld.com

innovation

Record, Replay, Rewind 28Testing GNSS Receivers with Record and Playback Techniques

Is there a way to perform repeatable tests on GNSS receivers using real signals? This month’s column looks at how to use an RF vector signal analyzer to digitize and record live signals, and then play them back to a GNSS receiver with an RF vector signal generator.By David A. Hall

»cover storY

OpiniOns &Departments

Out in Front 6Welcome to Accuracy AnonymousBy Alan Cameron

eXpert aDvice 8An EPIC Start for CoordinationBy John Wilde

the system 10GLONASS Forecast Bright and Plentiful; Future GPS Control Segment Advances; Power Flex Positive; Air Force Fends off GAO Zinger; New Galileo SIS ICD Embraced; FAA Green-Lights ADS-B.

Letters 13History Articles Set the Record Straight

the business 14NovAtel Releases OEM6 Receiver Platform; Ashtech to Use IFEN Simulator; Locata Covers White Sands Missile Range; Dual-Frequency miniEclipse; and more

survey

Sparse Network 44Wide-Area, Sub-Decimeter Positioning for Airborne LiDAR SurveysThe use of a precise wide-area positioning technique for airborne trajectory solutions for LiDAR surveys provides both relative and absolute accuracies similar to those derived from using a local GNSS reference station.By Oscar L. Colombo, Shane Brunker, Glenn Jones, Volker Janssen, and Chris Rizos

transpOrtatiOn

Can GNSS Drive V2X? 35Communication-enabled vehicle safety has the potential to change transportation’s future, particularly vehicleto-vehicle (V2V) and vehicle-to-infrastructure (V2I), collectively represented as V2X. An automakers’ consortium conducted extensive field trials to determine GNSS service availability and accuracy for the V2X challenge.By Chaminda Basnayake, Tom Williams, Paul Alves, and Gérard Lachapelle

www.gpsworld.com october 2010 | GPS World 3

ONLINE RESOURCES

Blogs from ION-GNSS 2010GPS World again provided exclusive live coverage of the ION-GNSS Conference, September 21–24 in Portland, Oregon. Visit gpsworld.com/ion for all the news and blogs. Here is one excerpt:

Military BoardsDefense Editor Don JewellThis year I have noticed a plethora of MIL STD (military standard) boards that are about the size to fit perfectly in a PCMIA slot. And none more intriguing than the MB 100 Compact dual-frequency RTK OEM board from Ashtech. Their new board fits this year’s theme of cooperation among current and future PNT providers in that it is GLONASS-capable. You may be aware that GLONASS has never been able to reach FOC or Full Operational Capability with their satellites due to the extremely short life span of their satellites. But the Russian Space Federation seems to have the longevity issues under control these days, at least according to their spokesman, Dr. Sergey Revnivykh, who claims — and I hope he is correct — that GLONASS will reach FOC with 24-plus working satellites on orbit in December of this year.

Hottest Pages @ GPSWorld.comAugust 31 – September 30, 2010

1 Air Force Reorganization May Drastically Affect GPS Program

2 GPS Flexible Power Coming

3 Sony Introduces Digital Camera with GPS and Compass

4 Spoofing Detection and Mitigation with a Moving Handheld Receiver

5 GNSS Almanac: Constellation Data

6 Innovation: Friendly Reflections

7 Innovation: Precise Point Positioning

8 ION-GNSS Live Coverage

9 Are You a Professional? (GSS newsletter)

10 2010 GNSS Buyers GuideFor times and pre-registration, see www.gpsworld.com/webinar

Check out These Recent Tech Talk BlogsGo to www.gpsworld.com/techtalk

Can GPS Modernization Be More Effective and Less Costly?By James L. FarrellA response to the August Expert Advice column “Remembering. And Resolving” by the mysterious Masked Engineer.

Context-Aware Navigation AlgorithmsBy Jussi Collin Assume that your mobile phone knows your mode of transportation (stationary, walking, riding a car, and so on) automatically. How could navigation algorithms take advantage of this information?

Tracking SVN-62 with a Triple-Frequency ReceiverBy Senlin Peng, Yanhong Kou, and Jade MortonFollowing the successful launch of the GPS Block IIF SVN-62 satellite on May 28, 2010, the Software GPS Receiver Laboratory at Miami University has been actively monitoring and analyzing the satellite signals. This article presents the tracking results of 300 seconds of L1, L2C, and L5 signals.

Don Jewell

Richard Langley

Eric Gakstatter

» OCTOBER WEBINARS

Location-Based ServicesOctober 22, 2010 Speaker: Lisa Peterson, Neustar

Highlights from the European Navigation ConferenceOctober 28, 2010 Speaker: Alan Cameron, GPS World

Commentary, audio, and video interviews from Braunschweig, Germany.

GPS World | October 2010 www.gpsworld.com4

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Hi, my name is Alan, and I’m an accuracy addict.

I got my first taste of accuracy back in 2000 when I started at GPS World, and discovered the vast range of very advanced things that people were doing with the signals of the Global Positioning System.

This filled me with a great feeling of elation, expansiveness, and effectiveness. I can position anything. I can track anything. I can go anywhere, and know where I am. I can direct something else to go somewhere, and have it hit exactly on target. I can examine the minute movements of the earth, the swaying of skyscrapers, the moisture content of the atmosphere, and I can know all.

I began to feel the illusion of omnipotence — of power over all.

The more I found out about accuracy,

the more I used it, the more addicted I became.

Very early, I learned that advanced practitioners, such as some of the people in this room, had developed ways of taking two GPS signals, not just one, but two signals, including one that they weren’t even entitled to use, and combining them, distilling them, refining them to produce an even more potent product: high precision.

High. I was getting pretty high. Almost as high as some of you.

Because we’re all in this together. In this room, we are all addicts. And when our supply of accuracy gets cut off, or restricted, or we learn that it might soon be diminished in some way, or even that its projected future rate of increase might not be as rapid as expected, or that it might not

increase at all, it might just simply stay the same — well then, we get upset.

We want to get high precision, we want to stay high precision, and we want to get higher precision.

We may have a problem with our accuracy habit.

It’s not just us, the highly educated, highly equipped, highly advanced users, with near-lifelong histories of accuracy use. Outside this room, outside this convention center and all who gather here this week, outside our offices and labs, the great unwashed masses are getting their first taste of low-grade accuracy. With their cell phones or smart phones, maybe 50-meter, maybe 15-meter, maybe even 5-meter accuracy.

They’re liking it, that first taste. Once they learn how to exploit it, and learn that higher accuracy is possible, they’re going to demand it.

And some enterprising young engineers are going to build a high-powered LBS app that needs high accuracy, just like other new apps need broadband or WiFi or 3G or 4G. If the capability exists, someone wants to make money off it.

We may be raising a generation of monsters, who will absorb our habit into their bloodstreams and into their lifestyles.

Things might get ugly. We know they’re going to change, altering the landscape in ways we may not recognize.

I’m not talking about just the social landscape, the way accuracy users behave. Not just the user segment. I’m talking about the way accuracy is produced and administered. I’m talking about the supply of accuracy, the supply of a substance that is in high demand and to which an increasing number of people are becoming addicted.

I’m talking about the ground control segment and the space segment.

Ultimately, I’m talking about who makes the decisions, who funds the

decisions, who enacts the decisions, and who enforces the decisions about how much accuracy can and will be produced.

Today, we know, or think we know who those people are: the GPS Wing, the Air Force, the Department of Defense, the Administration of the U.S. government. We may think we know that those same people will be in charge tomorrow.

I’m not so sure. Revolutions have happened before.

I don’t mean to be U.S.-centric. The same developments are taking place, perhaps a bit lagged, in Europe and Russia and China. When the great mass of the Chinese market gets into using accuracy, gets the habit, you’re going to see some effects.

Returning to the United States, simply because it has the most known and most established of these systems, it is not inconceivable that some Tea Party-like movement, a groundswell should roll right up to Washington, into Congress, and say:

“Higher accuracy is possible. We are paying for GPS with our taxes, and we want you to spend that money producing and supplying us with a higher grade of accuracy. Don’t give us this talk of responsible stewards. We are calling the shots now. Just do it. Revise the ICD. Up the ante.

“Give me accuracy or give me death.”Ladies and gentlemen, I have

expanded, exaggerated only slightly, and perhaps exploded the old dictum that I’ve heard attributed to Charlie Trimble, I don’t know who first said it, but it bears repeating and repeating often: accuracy is addictive.

Indeed it is. I’m here to tell you.I was asked to give you a user

perspective. I’ve chosen what is today a relatively small user segment, but a very real one, and a growing one. And most important, one that augurs for the future.

Perhaps the scenario I just imagined for you exaggerates a bit. Perhaps. I am consciously trying to push further out the boundaries of our thinking.

Continued on page 9

Welcome to Accuracy Anonymous

OUT IN FRONT

Today, we think we know who makes the decisions, who funds the decisions. That may change.

GPS World | October 2010 www.gpsworld.com

“ADDICTION” was delivered as an invited presentation at the Civil GPS Service Interface Committee plenary session, September 20 in Portland, Oregon.

6

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Published monthly

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www.gpsworld.com October 2010 | GPS World 7

®

The new European Positioning, Navigation, and Timing (PNT) Industry Council (EPIC) will

be a forum for organizations with an interest in all PNT systems including Global Navigation Satellite Systems (GNSS). EPIC shall serve as an informa-tion and distribution portal between all stakeholders in the PNT community. Its

mandate includes all GNSS constella-tions and related augmentation systems worldwide, both operational and in development/modernization.

EPIC will undertake to serve the interests of all stakeholders within Europe, and on behalf of Europe on the global stage, recognizing that understanding and cooperation between the world’s stakeholders is key to the successful deployment of new and improved GNSS applications. We also envision that EPIC will become a thriving forum for the exchange of new ideas and best practices, as well as becoming a knowledge center hosting working groups and task forces

focusing on specific GNSS issues. EPIC would thus not only serve as a gateway but actually assist stakeholders in developing common solutions to common problems in-house.

RepresentationGNSS has applications in many com-mercial and non-commercial fi elds: academia, agriculture, airline operators, civil aviation authorities, air navigation service providers, emergency services, energy suppliers, logistics, manufactur-ing, maritime, communications, pet-rochemical, rail, surveyors, and more. Therefore, EPIC will work on behalf of all GNSS stakeholders regardless of their application or business model and represents the whole community, inte-gral to the ongoing success of GNSS. In addition it will represent the needs of users and developers of downstream applications.

InternationalEPIC stands with sister organizations in North America and Asia:� United States GPS Industry Council � Japan GPS Council� Korean GNSS Technology Council

EPIC will maintain close ties to these organizations and will profit from shared practices and knowledge when mutually beneficial. Joint representation with these organizations to government GNSS authorities will be a key coordination activity.

CommunicationEPIC will encourage communication and cooperation among its member-ship to develop new associations and partnerships to create new applications or share ideas and expertise. It will or-ganize regional meetings, workshops, focus groups and social gatherings.

EPIC is intended as a forum — not

just a place for debate but literally

a marketplace of ideas where real

transformative change can take place.

EDITORIAL ADVISORY BOARD

Vidal Ashkenazi Nottingham Scientific Ltd., United Kingdom

Sally Basker General Lighthouse Authorities, United Kingdom & Ireland

Alison K. Brown NAVSYS Corporation, United States

Pascal Campagne France Developpement Conseil, France

Ismael Colomina Institut de Geomàtica, Spain

Jordi Corbera Spanish Institute of Navigation, Spain

Nicolas de Chezelles Ministry of Defense, France

Clem Driscoll C.J. Driscoll & Associates, United States

Børje Forssell Norwegian University of Science and Technology, Norway

Alain Geiger Institute of Geodesy and Photogrammetry, Switzerland

Art Gower Lockheed Martin, United States

Sergio Greco Alcatel Alenia Spazio, Italy

Jörg Hahn European Space Agency, The Netherlands

Michael Healy Astrium Limited, United Kingdom

Günter Hein University of the Federal Armed Forces, Germany

Larry D. Hothem U.S. Geological Survey, United States

Len Jacobson Global Systems & Marketing, United States

William J. Klepczynski Institute for Defense Analyses, United States

Gérard Lachapelle The University of Calgary, Canada

Wolfgang Lechner Telematica, Germany

Jingnan Liu National Research Center for Satellite Systems, China

Pietro Lo Galbo European Space Agency, The Netherlands Keith D. McDonald NavtechGPS, United States

Terence J. McGurn Consultant, United States

Jules G. McNeff Overlook Systems Technologies, United States

James Miller NASA, United States

Terry Moore University of Nottingham, United Kingdom

Ruth Neilan Jet Propulsion Laboratory, United States

Bradford W. Parkinson Stanford University, United States

Ivan G. Petrovski iP Solutions, Japan

Mario Proietti TechnoCom Corporation, United States

Jayanta Ray Accord Software and Systems, India

Martin U. Ripple European Aeronautics Defense and Space, Germany

Michael E. Shaw Lockheed Martin Space Systems, United States

Giorgio Solari Galileo Supervisory Authority, Belgium

Jac Spaans European Group of Institutes of Navigation, Netherlands

Thomas Stansell Jr. Stansell Consulting, United States

F. Michael Swiek U.S. GPS Industry Council, United States

David Turner Department of State, United States

A.J. Van Dierendonck AJ Systems, United States

Frantisek Vejrazka Czech Technical University, Czech Republic

Akio Yasuda Tokyo University of Marine Science & Technology, Japan

By John Wilde


EXPERT ADVICE

An EPIC Start for Coordination

ADVISORS UPDATE

TERRY MOORE directs the GNSS Research and Applications Centre of Excellence (GRACE) and the Institute of Engineering Surveying and Space Geodesy (IESSG), which has been significantly involved in many major Galileo projects, most recently SISTER (Centimetre positioning via SatCom) as part of EC FP6, the PRECISIO software-defined radio multi-GNSS receiver, ENCORE, and TESTCASE (all for EC/GSA).

The organization will update members on the latest developments within GNSS and work to ensure that information is made available in a sensible, secure manner and shared as publicly as possible. We intend to keep EPIC a dynamic organization, reflecting the world of GNSS, responsive and adaptable to the needs of its members. Therefore, active involvement from the membership of EPIC will be crucial to its success in both setting the agenda and then realizing it. It is no accident that EPIC is intended as a forum — not just a place for debate but literally a marketplace of ideas where real transformative change can take place.

To get the ball rolling, EPIC will conduct a market survey over the next few months with potential members to clarify their requirements and ensure that EPIC starts with the issues and people that matter.

For further details, www.epicforum.org, or contact [email protected]. �

JOHN WILDE has longtime experience in the GNSS field, specializing most recently in aviation requirements. He is the founder of EPIC. See also his February 2008 interview in this magazine on this same subject, at www.gpsworld.com/epic.

EXPERT ADVICE


Accuracy Anonymouscontinued from page 6

We’ve been waiting, some of us, for a long time for the mass market to get involved in GPS. This is now happening, bit by bit. But it has not yet fully happened. When it does, great changes will come. When LBS figures out the key to making money out of location, you’ll see changes you can’t imagine today.

I started to become aware of how pervasive and how strong accuracy addiction has grown when we experienced a succession of anomalies in the GPS constellation over the last year or so: SVN-49, the last IIR-M satellite; carrier-phase anomalies detected on SVN-48; and now SVN-62, a small variance in the L5 signal on the first IIF. “The signal variation results in no more than a 5-centimeter error with a predictable periodicity of about six hours.”

In each case, GPS performed within spec, and some therefore viewed these issues as non-issues. “What seems to be lacking is context: what relevance their findings on unspecified and unrequired signal characteristics really have to do with the real-world GPS IIF mission and requirements.”

I’ve repeated here two printed quotes in the magazine; offline, the point-counterpoint discussion grew a good deal more inflamed. Passions run high when

the supply and quality of accuracy appears in question.

This might seem a minor flare-up today, off in a corner of the field: specialized scientific research spatting with industry giants and their military-industrial complex benefactors.

But today’s developing applications in aviation, ground transportation, structural monitoring, machine control, infrastructure, and more use techniques such as carrier phase that are not governed, are not even mentioned in the GPS ICD.

When LBS gets figured out, and high-accuracy LBS and vehicle navigation and crash avoidance become regularly supplied commercial services, when the dependence of f inancial and communications infrastructure on high precision becomes fully understood and appreciated, then you’ll see some large corporate money that has become accuracy-addicted. Imagine this room in another few years, with GM, Ford, Google, Microsoft, AT&T, and Verizon attending and very interested, very much so, in aspects of user accuracy that are not currently addressed in the ICD.

This community will change. Its needs will change. Balances of power and funding will shift. Are we prepared for that? Are we prepared to be surprised? Or are we prepared only to be left behind by tides of change, to become obsolete? �

A giant container terminal in the port of Antwerp.

It’s hard to imagine a more complex day-to-day reality than that!

Around the clock, massive freights are shipped,

unshipped and moved around the terminal.

What could well be a logistical nightmare, now runs smoothly

with the aid of Septentrio’s ultra-precise positioning techniques.

Why?

Because we are reliable experts.

Because we are ahead.

“Th anks to Septentrio GPS technology,

we can run 24/7 operation

with 0 misplaced containers.”

Stephan Gosiau, Technical Director

PSA HNN

Policy and system news and developments | GPS | Galileo | GLONASS

SYSTEMTHE


A t the Civil GPS Service Inter-face Committee meeting in Portland, Oregon, on Sep-

tember 20, Sergey Revnivykh, Dep-uty Director General of Roscosmos’s Central Research Institute of Machine Building, reported on the status and future of GLONASS.

He provided a number of details on the present constellation and how it will be augmented in the future, stress-ing that GLONASS is doing well and that a full constellation of 24 primary satellites will be in operation within months. The average signal-in-space range error has improved by a factor of five in the past three years and pres-ently stands at about 1.8 meters (one sigma).

The present constellation consists of 20 healthy satellites with two reserve satellites, GLONASS 714 and 726. Revnivykh stated that GLONASS 726 had a failure of its navigation payload.

It is known that the signal generator on the satellite is faulty and it had been set unhealthy since August 31, 2009. Nevertheless, it was placed in reserve status on March 19, 2010. GLONASS 714 is nominally healthy and could be brought back to service if needed. These initial reserve satellites are also being used to train the ground team to operate spare satellites in a full or nearly full constellation.

GLONASS 727, in orbital slot 3, which was taken out of service on September 8, has also had a failure of its navigation payload and may not be returning to service. The three new satellites launched on September 2 are expected to enter service in early October. About 11 more GLONASS-M satellites will be launched by the end of 2012.

Revnivykh announced that there will be two versions of the new GLONASS-K satellites: GLONASS-K1

and GLONASS-K2. GLONASS-K1 satellites will have a 10-year design life and a daily clock stability of 5 � 10-14.

The first GLONASS-K1 satellite will be launched this December from the Plesetsk Cosmodrome about 800 kilo-meters north of Moscow. This will be the first launch of a GLONASS satellite from other than the Baikonur Cosmo-drome. Only one more GLONASS-K1 satellite will be built and launched after that. The K1 satellites will test an open service CDMA signal on the GLONASS L3 frequency in the 1205 MHz band. Although the launch of the first GLONASS-K1 satellite will occur in December, the design process for the CDMA signal structure is not yet finished, according to a subsequent e-mail message from Dr. Revnivykh. When the process is completed, the structure will be made public.

A completely new design, GLONASS-K2, will start launching in 2013. GLONASS-K2 satellites will have a 10-year design life and a daily clock stability of 1 � 10-14. Besides the CDMA signals on L3, CDMA signals will also be transmitted on L1 and L2. The GLONASS-K satellites will transmit the legacy FDMA satellites in addition to the CDMA signals.

A modernized GLONASS-K satel-lite, GLONASS-KM, for launch after 2015, is now under study. In addition to transmitting legacy FDMA signals on L1 and L2 and CDMA signals on L1, L2, and L3, CDMA signals may also be transmitted on the GPS L5 frequency at 1176.45 MHz. Also being studied is an alternative to the present three-plane, equally spaced satellite constel-lation. A different constellation design would be possible using CDMA sig-nals. Such a move would require that

GLONASS Forecast Bright and Plentifulby Richard Langley

▲ FIGURE 1 The GLONASS satellite generations through GLONASS-K2.

THE SYSTEM


the legacy FDMA signals be switched off. Revnivykh stated that any such move would require at least 10 years’ advance notice.

The signals that will be transmitted by the future generations of GLONASS satellites as well as those transmitted by the initial GLONASS satellites and the GLONASS-M satellites now on orbit are shown in FIGURE 2.

Revnivykh also spoke on the satel-lite-based augmentation system under development, System for Differential Correction and Monitoring (SDCM). Correction and integrity data will be transmitted by Luch geostationary communication satellites now under development. Luch 5A, to be launched in 2011 and positioned at 16°W longi-tude, and Luch 5B, to be launched in 2012 and positioned at 95°E longitude,

will transmit signals on an L1 fre-quency. Luch 4, to be launched in 2013 and positioned at 167°E longitude, will transmit on two frequencies. The three satellites will provide almost global cov-erage. The satellite payloads are under development.

According to Revnivykh, the SDCM will make use of 12 monitor stations currently in operation in Russia and one in Antarctica at Russia’s Bellingshau-sen research station. However, the SDCM website (www.sdcm.ru) indicates only 10 Russian stations currently in the test network. This anomaly might be explained by the fact that some lo-cations have multiple monitor stations. Eight more monitor stations will be added in Russia and five more outside Russia. Revnivykh showed a map revealing the locations of the additional

overseas stations as Cuba, Brazil, Viet-nam, Australia, and an additional sta-tion in Antarctica. It is not intended, at least initially, that these stations would be used in generating the orbit and clock data broadcast by the GLONASS satellites themselves.

Finally, Revnivykh stated that a GLONASS performance document will be released in the 2012–2013 time frame. His full presentation is available on the U.S. Coast Guard Navigation Center website (www.navcen.uscg.gov).

Meanwhile, the three GLONASS-M satellites launched on September 2 have arrived at their designated orbital slots: GLONASS 736, plane 2, slot 9; 737, plane 2, slot 12; 738, plane 2, slot 16.

The operating frequencies are not yet fully known. GLONASS 736, in physical slot 09, is currently undergo-ing experimental tests. It is included in the broadcast almanac at slot 16 and is transmitting on frequency channel �6. Stations in the International GNSS Ser-vice ground network are tracking the satellite. According to the Roscosmos Information-Analytical Centre, when the tests are completed, GLONASS 736 will transmit on channel �2 and be identified as slot 09 in the almanac. It is unclear if GLONASS 736 will replace GLONASS 722 also currently in slot 9, with the latter becoming a spare, or if GLONASS 736 will become the spare as previously inferred.

GLONASS 737 and 738 have not started normal transmissions. Their assigned shared frequency channel is not yet known but �6 would be a likely candidate.

▲ FIGURE 2 Signals transmitted by the different generations of GLONASS satellites. OF � open-access FDMA, SF � special (military) FDMA, OC � open-access CDMA, OCM � open-access CDMA modernized.

The Raytheon Company team developing the next-generation GPS Advanced Control Segment (OCX) successfully completed on schedule an integrated baseline review with the U.S. Air Force.

When completed, GPS OCX will deliver a control seg-ment designed to provide secure, accurate, and reliable

navigation and timing information to military, commercial, and civil users. Raytheon is the prime contractor on the $886 million program. The team includes ITT, The Boeing Company, Infinity Systems Engineering, Braxton Technologies, and NASA’s Jet Propulsion Laboratory.

Future GPS Control Segment Advances


THE SYSTEM

New Galileo ICD Embraced European Commission (EC) officials held a briefing during ION-GNSS in Portland for industry representatives, to discuss the new Galileo Open Service Signal-in-Space Interface Control Document (OS SIS ICD). Hosts Paul Verhoef and Michel Bosco said they were pleased with what they character-ized as positive feedback from U.S., European, and Japanese industry repre-sentatives regarding collaboration and consultation over changes made in the ICD. The updated version is available at http://ec.europa.eu/enterprise/policies/satnav/galileo/open-service/index_en.htm.

The EC grants free access to the technical information on the future Galileo open service signal: the specifications manufacturers and developers need to process data received from satellites. Anyone who wishes to use the intellec-tual property rights contained in the document simply needs to send an e-mail to [email protected] mentioning their request for a license agreement, which is without any exclusivity or geographic limitation.

Power Flex PositiveFrom September 7 to 12, the U.S. Air Force Space Command (AFSPC) activated the long-awaited Flex Power demonstration for GPS, a power increase on L1 and L2. The trial of a new capability designed for military use under special circumstances was deemed a success, essentially going off without a hitch, according to Colonel David Buckman, AFSPC Com-mand Lead for PNT, and Colonel Ber-nie Gruber, GPS Wing Commander.

Officially, the flex power assess-ment ensured that the GPS control segment baseline (AEP 5.5) is properly integrated with the space segment with regard to command and control of High-Y Flex Power, a capability that

increases the nominal transmit power of the desired signal by shifting power between signals (M-code and P(Y)) within a particular L-band. The net sum gain remains the same. High-Y Flex Power does not change total transmit power, does not affect phase stability between L1 and L2, is ICD-GPS-200E compliant, and does not affect the navigation message.

Only a handful of 10-year-old reference receivers may have been adversely affected, possibly due to an outdated algorithm. Many govern-ment, commercial, and civil agencies were involved in the test, and hundreds of GPS receivers were closely monitored. As far as impacts

to the overwhelming majority of global users, it was a non-event. The 2nd Space Operations Squadron (2SOPS) was able, over the course of five days, to make power changes to several GPS satellites without causing a phase shift and without the majority of users even knowing what was happening, although various announcements and press releases had appeared to alert them of the fact.

All GPS satellites and signals have now returned to their normal power levels.

Air Force Fends off GAO ZingerThe U.S. Government Accountability Office has issued a follow-up to its alarming and much-criticized report, issued 16 months ago, on the health and prospects of the GPS constellation. Senior officers at the Air Force Space Command and Space and Missile Systems Center have characterized the new report as “overly pessimistic.”

The report’s principal findings — that the Air Force continues to face challenges in launching its satellites as scheduled, which could affect the availability of the baseline GPS constellation, that on-orbit performance of IIF satellites remains uncertain, that a disconnect exists between GPS III and OCX, and that a predicted possible delay in GPS III could affect GPS constella-tion performance — are discussed and rebutted in detail by GPS World defense editor Don Jewell, with further commentary (paraphrased) by Air Force Space Command, in his October column, at www.gpsworld.com/dejavu.

FAA Green-Lights ADS-BThe U.S. Federal Aviation Administra-tion (FAA) gave the go-ahead signal for full-scale, nationwide deployment of the satellite-based surveillance system called Automatic Dependent Surveil-lance – Broadcast (ADS-B) following its successful roll-out at four key sites. Air traffic controllers are now able to use the new technology to separate aircraft in areas with ADS-B coverage. Controller screens in those areas will show aircraft tracked by radar as well as aircraft equipped with ADS-B avion-ics, which broadcast their positions.

The new system tracks aircraft with greater accuracy, integrity, and reliability than the current radar-based system, the FAA said. ADS-B targets on controller screens update more frequently than radar and display infor-mation including aircraft type, call sign, heading, altitude, and speed.

Nationwide ADS-B coverage is scheduled to be complete in 2013. According to the FAA, every part of the country now covered by radar will have ADS-B coverage. More than 300 of the approximate 800 ADS-B ground stations that will comprise the entire network have been installed.

By 2020, aircraft flying in controlled airspace in the U.S. must be equipped with ADS-B avionics that broadcast their position. �

Iwas relieved to see that the facts related to the conception of GPS were clearly laid out in the two-part article “GPS

Heroes” (May and June issues). During the past few years, erroneous information about the early years of GPS development has circulated in some military, engineer-ing, and scientific circles. These stories centered on some version of the idea that GPS’ design originated with the Naval Research Laboratory (NRL) and within the patent submitted for Timation by the NRL’s Roger Easton; the U.S. Air Force and The Aerospace Corporation were conspicuously missing from the various scenarios that credited Roger Easton with “inventing” GPS.

I have had the privilege to record and publish oral history interviews with several GPS pioneers, including Drs. Getting and Parkinson and Ed Lassiter. I also had opportunities to speak to many more early GPS participants off the record, including retired Air Force personnel and several non-Aerospace employees, when conduct-ing background research for an article dealing with the beginnings and subsequent implementation of GPS.

My research included a review of many of the primary documents relating to GPS’ origins, including the Woodford/Naka-mura study completed for 621B in 1966, and several subsequent studies. I can state emphatically that during the course of my research, I never encountered any evidence indicating that NRL’s/Easton’s Timation system was the progenitor of GPS. In fact, as the authors point out, Timation was considered and rejected by 621B personnel when planning the original system.

Not a single person I spoke to has ever provided me with any version of GPS’ genealogy other than the one related by Parkinson and Powers. The majority of the interviewees, on or off the record, gave NRL and Mr. Easton ample praise for their significant contribution to satellite navigation through the development of the Timation system; no one even remotely carried this acknowledgement and appreciation of Timation as an antecedent to GPS any further, historically speaking. After discussing Timation with several

interview subjects familiar with the system, it became clear there was a general consensus that Timation simply did not have the necessary capabilities to meet the requirements for the GPS design that was ultimately selected.

With the publication of Parkinson’s and Powers’ article, GPS World has provided

an excellent public forum for the presenta-tion of the facts, not the folklore, regarding the historical origins of GPS, clearly and in detail for the GPS community.

Steven StromEl Segundo, California

LETTERS TO THE EDITOR


History Articles Set Record Straight

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Trimble GNSS OEM Systems: Performance You Can Rely One GNSS OEmble GT

www.trimble.com/GNSS-Inertial

» PROFESSIONAL OEM

Industry news and developments | GPS | Galileo | GLONASS

BUSINESSTHE

NovAtel Inc. has announced its OEM6 GNSS receiver platform, which the company says offers comprehensive support for all current and upcoming GNSS constellations and satellite signals, including GPS, GLONASS, Galileo, and Compass. The first in a new receiver line, OEM6 expands positioning capabilities with the inclusion of such features as receiver autonomous integrity monitor-ing (RAIM) for safety-critical applications, integrated LAN Ethernet port with NTRIP client and server capabilities for integration into reference network applications, and 100-Hz measurements for high-dynamic positioning.

The OEM628 board is form-, fit-, and function-com-patible with the company’s earlier OEMV-2 receiver. All

NovAtel OEM firmware options are supported, including AdVance RTK for centimeter-level positioning accuracy, ALIGN for precise heading determination, GL1DE for consistent pass-to-pass accuracy, and L-band position-ing for autonomous decimeter-level positioning.

The OEM628 will be available to order in November, with first shipments in December.

NovAtel Releases OEM6 Receiver Platform

Ashtech Adopts IFEN Simulator for Development and TestingAshtech has selected the NavX-NCS Professional, a multi-constellation and multifrequency GNSS RF navigation constellation simulator from IFEN GmbH, as the GPS, Galileo, and GLONASS reference simulator for its profes-sional receiver development and testing.

IFEN offers two types of GNSS RF constellation signal simulators for GNSS testing needs and applications. The NavX-NCS Professional, optimized for research and devel-opment of multi-frequency GNSS safety and professional applications, has up to 108 signal channels and 9 L-band frequencies. GPS, Galileo, GLONASS, and QZSS can be simulated simultaneously. A Standard model, focused on system integration and production testing for L1 mass market applications, carries up to 36 channels and sup-ports all GNSS, including WAAS, EGNOS, and MSAS, at L1 upper frequency.

Igor Grechkin, Ashtech head of engineering, cited the NavX-NCS Professional’s flexibility in use, high accuracy, and upgrade capability as reasons for the selection. Ashtech launched its first high-precision GPS receiver in 1987 and plans to use the IfEN’s simulator to expand its high-precision professional portfolio.

Locata Covers White Sands Missile Range for 746 Test SquadronThe U.S. Air Force 746 Test Squadron awarded a contract to Locata Corporation to upgrade the Locata high-accu-racy terrestrial positioning system to cover almost 2,500 square miles (6,500 square kilometers) of the White Sands Missile Range in New Mexico. The upgrade is designed to help the 746 TS provide sub-meter accurate positioning on the test range when GPS is jammed. The contract focuses on the redesign and upgrade of the Air Force’s current Locata Non-GPS Based Positioning Sys-tem, sold commercially under the LocataNet brand.

The network will give the 746 TS’s Ultra High Accuracy Reference System (UHARS) sub-meter position accura-cies in a GPS-denied environment. The 746 TS requires UHARS to evaluate performance accuracies of next-generation weapon and aircraft navigation systems. The 746 TS leads the U.S. Department of Defense GPS Test Center of Expertise and has operated a Locata NGBPS at Holloman Air Force Base for more than three years.

Locata says its patented TimeLoc technology enables autonomous synchronization of LocataNets to picosec-ond level without atomic clocks or any form of external aiding. Other Locata partners include Leica and Trimble.


Hemisphere GPS Dual-Frequency miniEclipse Hemisphere GPS has announced its miniEclipse, a compact dual-frequency GPS OEM board that incorpo-rates the same digital and analog ASIC design as the recent Eclipse II OEM board. The miniEclipse is available in two form factors, P200 and P201, the former a drop-in board replacement for Hemisphere GPS’ Crescent board, the latter configured as a drop-in replacement for another industry standard interface.

Both receivers offer high-performance positioning ac-curacy and low-power consumption in a tiny package, the company said. miniEclipse functions in L1-only SBAS and RTK modes and can be upgraded to dual-frequency real-time kinematic (RTK) solutions. Also, raw data is available for post-processing in any configuration. Cres-cent module integrators can easily transition to dual frequency by replacing it with miniEclipse P200, adding a few new messages, and then connecting a dual-fre-quency antenna such as the A52TM, according to the

company. The receivers

also feature Sure-Track technology to increase RTK performance. The miniEclipse-enabled rover makes use of every satellite it is tracking, even satel-lites not tracked at the base. In addition to better cycle slip detection, this provides for faster RTK reacquisition and greatly improved RTK robustness. Reli-able DGPS positioning is enhanced through Hemisphere GPS’ COAST technology.

The two OEM boards will be available in the fourth quarter of 2010.

» PROFESSIONAL OEM/SURVEY

THE BUSINESS


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u-blox, a fabless semiconductor pro-vider of embedded positioning and wireless communication solutions, has purchased Spirent’s GSS6700 Multi-GNSS constellation simulator system to demonstrate performance of its new Galileo chipset. Using the simulator, u-blox recently dem-onstrated the attributes of its latest GPS/Galileo receiver to a number of its Japanese customers.

“Spirent is seeing an increasingly positive attitude to Galileo, following several Galileo system procurement announcements made earlier this year,” said John Pottle, marketing director at Spirent’s positioning unit. “The industry is starting to believe in Galileo again and we are seeing that confidence translate into investment decisions in Spirent multi-GNSS so-lutions.”

u-blox has been a Spirent cus-tomer since 2004. According to Tesshu Naka, u-blox’s Japan country manager, “The ability to demonstrate u-blox Galileo-ready technology before the satellites are available is a convincing argument in favor of u-blox receivers.”

Only simulators can fully test par-tially deployed GNSS constellations such as Galileo and QZSS, and future signals such as L5 and L2C on GPS. Until recently, most testing focused on GPS, but with GLONASS operat-ing at near full strength and Galileo and Compass around the corner, testing multi-GNSS capabilities on chipsets and navigation devices is becoming critical to verify perfor-mance and ensure there are no inter-operability issues, u-blox stated.

» CONSUMER OEM

u-blox Demonstrates Galileo Chipsets with Spirent Simulator

NovAtel’s 1.011 Firmware Release for its OEMStar L1 GNSS receiver reduces the card’s power con-sumption. The OEMStar receiver now consumes only 450 mW for GPS+GLONASS operation and 360 mW for GPS-only operation.

The update aids battery-powered applications such as handheld GIS data collectors, smart survey anten-nas, and even some unmanned vehicles, the company said. The 14-channel OEMStar receiver, NovAtel’s lowest cost, high-perfor-mance L1 GNSS receiver, uses L1 GPS, GLONASS, and SBAS signals. NovAtel’s GL1DE technology is also available.

By providing this functionality as

a firmware update, customers can apply it to their existing receivers, en-abling quick changeover and minimal downtime, free of charge to NovAtel customers, the company said.

» PROFESSIONAL OEM

NovAtel Cuts Power Use for OEMStar L1 Receiver

Linx Technologies announces its DB1-LP Series of gain antennas. These tri-band log periodic antennas are designed for long-distance directional communication over a multitude of frequencies. The DB1-LP antenna provides gain and directivity compa-rable to a Yagi antenna, but in a much smaller form factor and over a wider range of frequencies.

» WIRELESS

Tri-Band Antenna


THE BUSINESS

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Septentrio Receiver Spearheads Scintillation Research » SYSTEM DESIGN

Septentrio has rolled out PolaRxS, an ultra-low-noise multi-frequency multi-constellation receiver dedicated to ionosphere monitoring and space weather applications.

PolaRxS offers 136 channels capable of tracking simul-taneously GPS, GLONASS, Galileo, and SBAS signals in L1, L2, L5 and E5ab/AltBOC bands. Coupled with an oven-controlled crystal oscillator, the receiver provides an extensive set of specific measurements for ionosphere monitoring, including signal phase and intensity at up to 100 Hz, with a phase-noise standard deviation (phi60) as low as 0.03 rad.

Proprietary technology guarantees robust tracking of rapid signal dynamics encountered during high scintil-lation events, while the integrated interference analysis and mitigation module enables installation in difficult radio environments, according to the company.

A graphical user interface provides data logging and remote control. Specifically for space weather and ionosphere monitoring applications, the logging tool is extended for continuous TEC and scintillation indices (ISMR) logging and monitoring. The interface and receiver on-board Internet connectivity enable deployment of monitoring networks at minimal installation and mainte-nance cost, while its sturdy waterproof housing and low system power consumption (5W) make installation of autonomous stations possible in harsh environments.

“With the currently increasing solar activity heading to a max forecasted in 2013, combined with increasing reli-ance on satellite communication and GNSS technologies,

ionosphere monitoring and space weather vigilance are becoming of crucial importance,” stated Peter Grognard of Septentrio. “PolaRxS has been developed in close col-laboration with prominent members of the ionosphere sci-ence community to provide a state-of-the-art tool to deploy most effective, low infrastructure-cost, multi-frequency ionosphere and space weather monitoring networks.”

Septentrio will start shipping PolaRxSTM in the last quarter of 2010.

Brazil Partners. In related news, the European Galileo R&D Framework Programme (FP7) and the European GNSS Supervisory Authority (GSA) granted co-funding to the CIGALA Consortium, led by Septentrio, to develop and test receiver-level ionospheric scintillation mitigation to increase the robustness of professional multi-fre-quency GNSS based applications in low latitude regions, particularly in Latin America.

Solar induced ionosphere activity may lead to the scin-tillation of the GNSS signals that not only can degrade signal quality but also cause signal outage. The problem is particularly acute in low-latitude areas and will be exacer-bated with the next solar maximum. Latin America relies to a great extent on GNSS in support of activities such as land and offshore surveying, and therefore is particularly exposed. A Euro-Brazilian consortium of Septentrio, the University of Nottingham (UK), INGV (Italy), Pildo Labs (Spain), and Brazilian partners Petrobras, Universidade Estadual Paulista Julio de Mesquita Filho and Consultgel will pursue collaborative research.

L-3 Will Add GPS Capabilities to U.S. Army IPADS

» DEFENSE

L-3 Communications announced that its Space & Naviga-tion division has been awarded a four-year, indefinite-delivery/indefinite-quantity contract by the U.S. Army for adding GPS capabilities to its fielded Improved Position and Azimuth Determining Systems (IPADS) equipment.

IPADS is a high-performance, highly accurate system used for precision surveying and navigational require-ments on the battlefield. Under the contract, L-3 will design, implement, and test Selective Availability Anti-Spoofing Module (SAASM) GPS receivers, antennas, and cables into all fielded IPADS equipment. The GPS-equipped systems will be known as IPADS-G.

“The addition of an embedded, tightly coupled GPS capability will provide an excellent performance enhance-ment for long-distance precision survey operations by keeping the soldier on the move, while retaining a high level of inertial precision for GPS-denied conditions,” said Paul Wengen, president of L-3 Space & Navigation.

Anthony Giles, U.S. Army product manager, IPADS, for the Joint Lightweight 155mm Program Office, added, “The IPADS-G capability is essential in the delivery of accurate fire support to our maneuver forces, enhancing their ability to fight the global war on terrorism.”

THE BUSINESS


» GOVERNMENT

Ricoh Co., Ltd. has released the G700SE with GPS, Wi-Fi, and Bluetooth. As an expanded func-tion model of the G700 released earlier this year, the water- and dust-resistant G700SE has wire-less LAN and Bluetooth functions as standard features and supports the use of GPS and laser barcode-reader functions with options.

By installing the optional internal-electronic-compass-equipped GPS unit, users can add position and direction information to their photos. By installing the optional laser barcode-reader unit, users can do rapid recognition of one-dimensional (linear) barcodes. Ricoh states these capabilities make the G700SE a powerful tool for a wide range of operations, including facility maintenance (elec-tric, gas, and water utilities; roads; and so on), disaster planning, and other functions of local governments, po-lice departments, and fire departments; photo manage-ment in hospitals; production line management in the manufacturing industry; and warehouse management in the transport industry.

The G700SE can use the GP-1 (option) GPS unit which compactly connects to the camera body. Connection of the GP-1 makes it possible to add position information to the image data of photographs taken. In addition, since

there is an electronic compass function, it is possible to record information indicating the direction in which the photograph was taken. A GPS log function tracks camera movement. With the GP-1 attached, the G700SE satisfies IP64 dust and water resistance performance standards and shock resistance standards for a 1.2-meter drop, Ricoh said.

The camera body has an internal Bluetooth Ver.2.1+EDR function. The ability to do high-speed data communication with a wide range of Bluetooth-compat-ible devices enables receiving position data from highly precise GPS devices and transmitting image data to com-patible personal computers and smartphones. The inter-nal wireless LAN (802.11b/g) function supports the WPS button connection for easy wireless LAN connection set-tings. The G700SE can also transmit images via wireless LAN while receiving GPS data from Bluetooth-compatible external GPS devices.

Body size of the camera is 118.8 × 71.0 × 41.0 millime-ters, and body weight is approximately 286 grams.

Trimble introduced its new Juno SD handheld, an addition to the pocket-sized Juno series of durable, lightweight field computing devices with integrated GPS technology. The Juno SD handheld adds to core Juno functionality with an integrated 3.5G high-speed downlink packet access (HSDPA) cellular SMS and voice capability. Juno SD handheld users can now keep in contact using the new cellular voice capabilities, enabling users to call the office for the next job, provide live updates from the field, or make a call in case of an emergency. As a result, the Juno SD handheld eliminates the need to carry a sepa-rate mobile phone.

All Trimble Juno series models include integrated GPS, wireless LAN (Wi-Fi) and Bluetooth connectivity, a 3 megapixel camera, a 533 MHz processor, 128 MB of onboard memory, a MicroSD/SDHC memory card slot, an all-day battery, and a 3.5 inch display.

The Juno SD handheld is designed for GIS-enabled

organizations that require high productivity from their mobile field workforce, keeping them connected and in touch while removing the need for a separate camera, GPS data collector, PDA, and cellular phone, according to the company. All Juno series handhelds incorporate a high-sensitivity GPS receiver specifically designed to maximize position yields in challenging GPS environ-ments, such as under forest canopy and near buildings in urban areas.

Trimble reports that the Juno SD handheld is available in 10 languages for worldwide users and is fully compat-ible with Trimble’s range of mapping and GIS field and office software. Powered by Microsoft Windows Mobile operating system, Juno users have access to personal productivity tools such as Word Mobile, Excel Mobile, Internet Explorer Mobile, and Outlook Mobile, enabling exchange of data between the field and office.

Trimble Mapping Handheld Has Voice Communications» SURVEY & MAPPING

Ricoh G700SE Features GPS Plug-In


THE BUSINESS

Revolutionary is not a word to bandy ab2010 International Symposium on GPS/GNSS October 26-28, 2010, Taipei, Taiwanhttp://gnss2010.ncku.edu.tw/

The annual International Sym-posium on GPS/GNSS provides an open forum for researchers and engineers to exchange innovative ideas on GNSS systems, techniques, applications, and opportunities. The 2010 symposium will be organized by National Cheng Kung University, Taiwan.

Trimble Dimensions 2010November 8–10, 2010, Las Vegas, Nevadawww.trimbledimensions.com

Trimble will hold its international user conference at the Mirage Hotel in Las Vegas. The theme of Trimble Dimensions 2010 — Converge, Con-nect, Collaborate — provides insight into how the convergence of technol-ogy can redefine the way surveying, engineering, construction, mapping, GIS, geospatial, utilities, and mobile resource management professionals connect and collaborate to achieve success.

5th ESA Workshop on Satellite Navigation Technologies (NAVITEC)December 8–10, 2010, Noordwijk, Netherlandshttp://www.congrex.nl/10c12/

The 5th ESA Workshop on Satellite Navigation Technologies will be held December 8 to 10, 2010 at ESTEC, Noordwijk, Netherlands. The confer-ence centers on the theme “Multi-GNSS Navigation Technologies: The Beginning of a New Age.” In addition to multi-GNSS issues, the event will focus on signal design, signal process-ing, GNSS payload technology effects, and integration of navigation technolo-gies with communication services.

ION International Technical Meeting 2011January 24–26, 2011, San Diego, Californiawww.ion.org

ION International Technical Meet-ing 2011 (ION ITM 2011) will be held January 24-26, 2011, at the Catama-ran Resort Hotel in San Diego, Cali-fornia. A plenary session on robotics navigation is planned.

AfricaGEO: Developing Geomatics for AfricaMay 31–June 2, 2011, Cape Town, South Africahttp://africageo.org/

The first AfricaGEO Conference will be held in Cape Town at the Cape Town International Convention Cen-tre (CTICC) from May 30 to June 2, 2011. AfricaGEO is being organized by the South African Geomatics As-sociations, and enjoys the full sup-port of, PLATO, GISSA, Hydrographic Society of South Africa, Institute of Mining Surveyors of South Africa, the Association of Aircraft Operating Companies and the Department of Rural Development and Land Re-form.

» EVENTS

THE BUSINESS


1. Publication Title: GPS World

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Known Bondholders, Mortgagees, and Other Security Holders Owning or Holding 1 Percent or More of Total Amount of Bonds, Mortgages or Other Securities: Questex Media Group, LLC is the Mortgagor under a Note and Equity Agreement dated December 16, 2009, with various lenders as named therein from time to time. The agent for the lenders is: Credit Suisse, Agency Manager, One Madison Avenue, New York, NY 10010. Holders of 1.0% or more of Questex Media Group, LLC Mortgages or Other Securities as of September 1, 2010 are as follows: Aladdin Capital Management LLC, Six Landmark Square, 6th Floor, Stamford, CT 06901; CHIH/Harris Bank, 111 West Monroe Street/12 West, Chicago, IL 60603; Carlson Capital LP, 2100 McKinney/ Suite 1600, Dallas, TX 75201; Credit Suisse AG, 11 Madison Avenue, New York, NY 10010; GSO/Blackstone Group, 280 Park Avenue, New York, NY 10017; GE Equity, 201 Merritt 7, PO Box 5201, Norwalk, CT 06851; Global Leveraged Capital Management, LLC, 805 Third Avenue/20th Floor, New York, NY 10022; Aladdin Capital Management LLC, Six Landmark Square, 6th Floor, Stamford, CT 06901; ING Capital LLC, 1325 Avenue of the Americas, New York, NY 10019; NATIXIS, 9 West 57th Street, 35th Floor, New York, NY 10019; Orix Finance Corporation, 1717 Main Street, Suite 900, Dallas, TX 75201; Pennant Park Investment Corporation, 590 Madison Avenue/15th Floor, New York, NY 10022; MJX Asset Management LLC, 12 East 49th Street, New York, NY 10017; Wells Fargo Capital Finance, Inc., 2450 Colorado Avenue/Suite 3000W, Santa Monica, CA 90404

More events online: www.gpsworld.com/events

While GNSS simulators have long provided the de factotechnique for testing GPS receivers, radio frequency (RF) record and playback has emerged as an innovative method to introduce real-world impairments to GNSS receivers. In this article, we will provide a hands-on tutorial on how to test a navigation device using the record and playback technique.

Th e premise of RF record and playback is to capture GNSS signals off the air with a vector signal analyzer (VSA) and then replay them to a receiver with an RF vector signal generator (VSG). With recorded GNSS signals, one is able to introduce a signal that contains natural impairments — instead of an ideal signal — to the GNSS receiver. As a result, one can ob-serve how a receiver will behave in a real-world environment where interference, multipath fading, and other impairments are present.

A VSA combines traditional superheterodyne radio receiver technology with high-speed analog-to-digital converters and digital signal processors to perform a variety of measurements on complex modulated signals. It is widely used in the tele-communications industry as a test instrument. Digitized sig-nals can be recorded for future analysis. A VSG reverses the process, taking a digital representation of a complex waveform and, using digital-to-analog converters, generating an appro-priately modulated RF signal.

Recording GPS or GLONASS signals off the air can be done in a fairly straightforward manner. An RF recording system combines appropriate antennas, amplifi ers, and an RF signal

recorder (usually a VSA) to capture many hours of continu-ous RF signal. In such a system, the basic components include the RF front end, the RF signal-acquisition device, and high-volume storage media. A block diagram of a typical recording system is shown in FIGURE 1.

In the fi gure, the RF front end is designed to condition the GNSS signal in such a way that it can be captured — with maximum dynamic range — by the recording device. Th e re-cording device digitizes a given signal bandwidth, and then stores in-phase and quadrature (IQ) waveforms to disk.

In general, RF recording devices are designed to tune to a broad range of frequencies and can thereby record many dif-ferent types of signals. Th us, selecting the signal to record is as simple as setting the center frequency and bandwidth of the recording device. For example, to record the GPS C/A-code L1 signal, the center frequency should be set to 1575.42 MHz. Because each satellite generates the same carrier frequency, one can capture C/A-code signals from all satellites simply by cap-turing all signals within a 2.046 MHz (twice the code chip-ping rate) band around the carrier frequency.

By contrast, recording GLONASS signals requires slightly diff erent settings. Because the GLONASS constellation uses frequency division multiplexing, every satellite generates the same code, but each pair of antipodal satellites transmits at a unique center frequency. Th us, recording L1 signal informa-tion for the entire GLONASS constellation requires a recorder to capture signals that range from 1598.0625 MHz (channel �7) to 1605.375 MHz (channel 6). In order to capture the en-tire bandwidth of each satellite, a recorder is actually required to capture 1.022 MHz of signal for each carrier (again, twice the code chipping rate). Th erefore, the total recording band-width is actually 1597.5515 MHz to 1605.886 MHz, a span of 10.3345 MHz. On the RF signal analyzer, one can record GLONASS signals simply by setting the center frequency to 1601.71875 MHz, and the bandwidth to ≥ 10.3345 MHz.

Modern RF signal recorders are capable of recording both GPS and GLONASS C/A-code signals on a single wideband

Record, Replay, RewindTesting GNSS Receivers with Record and Playback Techniques

David A. Hall

Is there a way to perform repeatable tests on GNSS receivers using real signals? This month’s column looks at how to use an RF vector signal analyzer to digitize and record live signals, and then play them back to a GNSS receiver with an RF vector signal generator.


RF front end

LNA

RF signal acquisition

ADC &DDC

Storage media

ÅFIGURE 1 GPS receivers implement cascaded low-noise amplifiers. The RF signal acquisition block includes analog-to-digital conversion (ADC) and digital down conversion (DDC) to select the data of interest.


Signal Processing | INNOVATION

recording channel. For example, one of our RF signal analyz-ers is capable of recording up to 50 MHz of signal bandwidth. With this instrument, one can simultaneously record both GPS and GLONASS by setting the center frequency to 1590.1415 MHz and the bandwidth to ≥ 31.489 MHz. However, while RF recording systems can be used to capture a wide range of GNSS signals including GPS L1/L2/L5, GLONASS L1/L2, Galileo, and others, this article focuses primarily on the GPS C/A-code signal.

Setting up the RF Front EndThe trickiest aspect of recording GPS signals is the selection and confi guration of the appropriate antenna and low noise amplifi er (LNA). When connecting a typical off-the-shelf GPS passive patch antenna to a signal analyzer, the peak power in the GPS L1 band ranges from �120 to �110 dBm. Because the power level of GPS signals is small, signifi cant amplifi ca-tion is required to ensure that the VSA can capture the full

dynamic range of the signal.Th e simplest method to amplify an off -the-air GPS signal

so that it can be captured by an RF signal recorder is the com-bination of an active GPS antenna and one or more external LNAs. Note that many professional GPS antennas off er the best performance because they combine high element gain with an LNA and even pre-selection fi ltering, which improves the dynamic range of the RF recorder.

With the RF front end appropriately confi gured, one can verify system performance using a simple spectrum analyzer demonstration panel. Th e demo panel allows one to visualize the RF spectrum in the GPS L1 band. If all is set up correctly, the C/A-code GPS signal should be visually present on the display. FIGURE 2 illustrates a screenshot of the spectrum on a virtual spectrum analyzer display.

Note that visualizing the GPS signal in the frequency do-main with an RF signal recorder (or spectrum analyzer) re-quires careful attention to settings such as resolution band-

AS A PROFESSOR, I’m quite familiar with testing — of students, that is. It’s how we check their performance — how well they have mastered the course material. Outside academia, testing is also quite common. We have to pass a driving test before we can get a license. We might have to pass a physical fitness test before starting a job. And manufacturers have to test or stress their products to make sure they are fit for purpose. As David Ogilvy, the father of advertising once quipped, “Never stop testing, and your advertis-ing will never stop improving.” But it’s not just manufacturers who should

test products. Consumers, or their representatives, should test products on offer — not only to corroborate (or dispute) manufacturers’ claims but also to compare one manufacturer’s product against another. There’s a whole slew of magazines, television programs, and web resources devoted to testing and comparing everything from laundry detergent to automobiles. And GNSS receivers are no exception.

When we conduct tests, we are usually trying to get answers to certain questions — just like those posed to students on their exams. In testing GNSS receivers, what are some ap-propriate questions? When a receiver is turned on, how long does it take until the position of the receiver is determined? When a weak signal area is encountered, can the receiver still determine its position? If the signal is interrupted and then restored, how long does it take for the receiver to re-cover and resume calculating its posi-tion? And what is the position accuracy under different situations?

While we can certainly hook up an antenna to a receiver to get answers to these questions in a certain environ-ment on a certain day at a certain time

with certain signals, the scenario can-not be repeated — not exactly. If we tweak a receiver operating parameter, for example, we don’t know for certain whether any observed change is due to the tweaking or a change in the scenario. We could use a radio-frequency (RF) simulator — a device for mimicking the radio signals gener-ated by the satellites. This would allow us to define scenarios, including receiver trajectories, and to replay them as many times as necessary while varying the operating parameters of the receiver. Or we could modify the scenario from run to run. Such test scenarios could include those difficult to carry out with live signals such as determining how a receiver would perform in low Earth orbit. While ex-tremely useful, these are tests with simulated signals.

Is there a way to perform repeat-able tests on GNSS receivers using real signals? In this month’s column, we learn how to use an RF vector signal analyzer to digitize and record live signals, and then play them back to a GNSS receiver with an RF vector signal generator — a procedure we can repeat as often as we like.

We can digitize signals with a vector signal analyzer.

INNOVATION INSIGHTS with Richard Langley


INNOVATION | Signal Processing

width and averaging. Because the signal-to-noise ratio (SNR) of the GPS signal is so small, the settings shown in Figure 2 require a narrow resolution bandwidth (10 Hz) and sig-nifi cant averaging (20 averages per measurement record, so a 20-second interval for 1 Hz data). With these settings applied, one can easily visualize a modulated signal above the noise fl oor with approximately 1 MHz of bandwidth and centered at 1575.42 MHz. Th is signal is the GPS C/A-code. In Figure 2, the reference level of the signal analyzer was set to �50 dBm to reduce the noise fl oor of the instrument to the lowest pos-sible level. Note that setting the signal analyzer’s reference level provides a simple mechanism to adjust the front-end attenua-tion or amplifi cation. In general, RF signal analyzers provide the greatest dynamic range when the reference level of the in-strument matches closely with the average power of the signal connected to the front end. In this case, setting the reference level of our signal analyzer to �50 dBm removes all front-end attenuation, giving the analyzer a more optimal noise fi gure for signal recording.

Hardware ConnectionsWith the reference level appropriately set, it is important to properly confi gure the RF front end of the recording device. As previously mentioned, one can achieve the best RF record-ing results by using an active GPS antenna. The active antenna used in our experiment utilized a built-in LNA to provide up to 30 dB of gain with a 1.5 dB noise fi gure. (Recall that the noise fi gure is the difference in dB between the noise output of a device and the noise output of an “ideal” device with the same gain and bandwidth when it is connected to sources at the standard noise temperature — usually 290 K.) However, the LNA must be powered by supplying a DC bias to the RF connection. While there are several methods to supply the DC bias, we will look at two of the easiest methods.

Method 1: Active Antenna Powered by GPS Receiver. Th e fi rst method to power an active antenna is with a bias tee or DC power injector. Using this three-port component, a DC voltage (3.3 V in this case) is fed to its DC port, which applies the appropriate DC off set to the active antenna connected to the RF-in port while blocking it on the RF-out port. Th e de-vice gets its name from the fact that the three ports are often arranged in the shape of a “T.” Note that the precise DC volt-age one should apply depends on the DC power requirements of the active antenna. A diagram illustrating the connections is shown in FIGURE 3.

Observe in Figure 3 that one can use off -the-shelf hardware such as a programmable DC power supply to supply the DC bias signal. Also, one can use a generic off -the-shelf bias tee as long as it has bandwidth up to 1.58 GHz.

Method 2: Active GPS Antenna Powered by Receiver. A second method of powering the active GPS antenna is with the receiver itself. Most off -the-shelf GPS receivers use a single port to power and receive signals from an active GPS antenna, and this port is already biased with an appropriate DC volt-age. Combining an active GPS receiver, a power splitter, and a DC blocker, one can power an active LNA and simply record essentially the same signal as that observed by the GPS receiver. A diagram of the appropriate connections is shown in FIGURE 4. Some splitters incorporate a DC block on all but one of the output ports.

As FIGURE 4 illustrates, the DC bias from the GPS receiver is used to power the LNA. Th is method is particularly useful for drive tests because one can observe the receiver’s characteristics, such as velocity and dilution of precision, while recording.

Selecting the Right LNARecording GPS signals with generic RF signal recorders is pos-sible largely because external LNAs can be used to reduce the effective noise fl oor of the receiver. Today, one can fi nd off-the-shelf spectrum analyzers with noise fi gures ranging from 15 dB to 20 dB. One of our analyzers, for example, has a 15 dB noise fi gure while applying up to 60 dB of gain. By applying external amplifi cation to the front of an RF signal analyzer,

-96

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-110

-112

-114

-116

-118

-120

Pow

er (

dBm

)

1.57292G 1.574G 1.575G 1.576G 1.577G 1.57792GFrequency (Hz)

ÅFIGURE 2 GPS is visible in the spectrum only if a narrow resolution bandwidth is used. This spectrum was obtained with a center frequency of 1575.42 MHz, a frequency span of 4 MHz, a resolution bandwidth of 10 Hz, root-mean-square averaging with 20 averages, and a reference level of �50 dBm.

Active GPSantenna

DC biastee

LNA

DC powersupply

Vector signalanalyzer

DC + RF RF

DC

ÅFIGURE 3 This set-up shows the use of a DC bias tee to power an active GPS antenna.

Active GPSantenna Splitter

GPSreceiver

DCblocker LNA Vector signal

analyzer

DC + RF

DC + RF

DC + RF RF

ÅFIGURE 4 With a DC blocker, one can record and analyze the same GPS signals being tracked by a GPS receiver.



however, one can substantially reduce the noise fi gure of the RF recording system.

To calculate the total noise that will be added to the record-ed GPS signal, one must calculate the noise fi gure for the entire RF front end. As a matter of principle, the noise fi gure of the entire system is always dominated by the fi rst amplifi er in the system. Th us, careful selection of the fi rst and second stage LNAs is crucial for a successful signal recording.

We can calculate the noise fi gure of the RF recording system by using the Friis formula for noise fi gure, named for engineer Harald Friis, a Danish-American radio engineer who worked at Bell Telephone Laboratories. To use this formula, fi rst convert the gain and noise fi gure of each component to its linear equivalent; the latter is called the “noise factor.” For cascaded systems such as our RF recording system, the Friis formula provides us with the noise factor of the entire system:

nfreceiver = nf1 + nf2 −1

g1

+ nf3 − 1

g1g2

+K+ nfn − 1

g1g2 ...gn

(1)Note that both noise factor (nf ) and

gain (g) are shown in lowercase to dis-tinguish them as linear measures rather than logarithmic measures. Th e conver-sion from linear to logarithmic gain and noise fi gure (and vice versa) is shown in the following equations:

NFdB = 10 × log10 nf( ) (2)

nf = 10NFdB

10⎛⎝⎜

⎞⎠⎟ (3)

GdB = 10 × log10 g( ) (4)

g = 10GdB

10⎛⎝⎜

⎞⎠⎟

(5)An active GPS antenna using a built-

in LNA typically provides 30 dB of gain while introducing a noise fi gure that is typically on the order of 1.5 dB. Th e second part of the recording instrumen-tation provides 30 dB of additional gain as well. Th ough its noise fi gure is higher (5 dB), the second amplifi er actually in-troduces very little noise into the system. As an academic exercise, one can use the Friis formula to calculate the noise factor for the entire RF front end of the record-ing instrumentation. Gain and noise fi g-

ÅTABLE 1 Noise figures and factors of the first two components of the RF front end.

Stage Gain (dB) Gain (linear) NF (dB) NF (linear)Active antenna

30 1000 1.5 1.4125

LNA 30 1000 5.0 3.1623Signal recorder

60 1000000 15.0 31.623

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ure values are shown in TABLE 1.According to the calculations above, one can determine the

overall noise factor for the receiver:

nfreceiver = 1.4125 + 3.1623 −1

1000+ 31.623−1

1000000= 1.4147

(6)To convert noise factor into a noise fi gure (in dB), apply

Equation 2, which yields the following results:

NFdB = 10 × log10 nf( ) = 10 × log10 1.4147( ) = 1.507dB (7)As Equation 7 illustrates, the noise fi gure of the fi rst LNA

(1.5 dB) dominates the noise fi gure of the entire RF recording system. Th us, with the VSA confi gured such that the noise fl oor of the instrument is less than that of the input stimulus, one’s recording introduces only 1.507 dB of noise to the off -the-air signal.

Saving Data to DiskEach GNSS produces slightly varying requirements for an RF recorder’s signal bandwidth and center frequency. For the GPS C/A-codes, the essential requirement is to record 2.046 MHz of RF bandwidth at a center frequency of 1575.42 MHz.

In the tests described here, we set the IQ sample rate of our RF recorder at 5 megasamples per second (Ms/s). Since each 16-bit I and Q sample is 32 bits (or 4 bytes each), the actual recording data rate is 20 megabytes per second (MB/s) to en-sure the entire bandwidth was captured. Capturing more than 4 MHz of bandwidth is suffi cient to record the 2.046 MHz C/A-code signals.

Because one can achieve data rates of 20 MB/s or more with standard PXI controller hard drives (PXI is the open, PC-based platform for test, measurement, and control), one does not need to use an external redundant array of independent disks (RAID) volume to stream GPS signals to disk when us-ing a PXI recording system. In general, data rates exceeding 20 MB/s require the use of an external RAID volume. External RAID systems are capable of storing more than 600 MB/s of data and can be used to support wide bandwidth channels or even multi-channel recording applications. For example, the recording system shown in FIGURE 5 uses an external RAID volume for high-speed signal recording. Th is system combines PXI RF signal generators and analyzers with external ampli-fi ers and fi lter banks for a ready-to-use GNSS record and play-back solution.

In our tests, we decided to use a 320 GB USB drive for bet-ter portability. With a disk speed of 5400 revolutions per min-

ute, we were able to benchmark it ahead of time and observed that we were able to achieve read and write speeds exceeding 25 MB/s. Th us, we were easily able to use this disk drive and still record IQ samples at 5 MS/s (20 MB/s) when recording off -the-air signals. With the existing hard-drive setup, we could record more than 4 hours of continuous IQ signal. Note that capturing longer recordings simply requires a larger hard disk. By using a 2 terabyte RAID volume (the largest addressable disk size in the Windows XP operating system), we can extend our recording time to 25 hours. With this setup, we could also reduce the IQ sample rate to 2.5 MS/s (still suffi cient to cap-ture the GPS C/A-code signals) and extend the recording time to 50 hours.

Receiver PerformanceOnce the off-the-air signal of a GNSS band is recorded to disk, it can be re-generated and fed to a receiver using an RF signal generator. With an RF signal generator that is able to repro-duce the real-world GNSS signal, engineers are able to test a wide range of receiver characteristics. Because recorded signals contain a rich set of channel impairments such as ionosphere distortion and interference from other transmitters, design en-gineers often use recorded signals to prototype the baseband processing algorithms on a GNSS receiver.

In our case, we used a VSG directly connected to a GPS evaluation board. In the experiments described below, the re-ceiver’s latitude, longitude, and velocity were tracked over time. Data was read from the receiver using a serial port, which read NMEA 0183 sentences at a rate of one per second. NMEA 0183 is a standard protocol developed by the National Marine Electronics Association for communications between marine electronic devices. NMEA 0183 has been adopted by virtually all GPS receiver manufacturers. In our LabVIEW graphical

ÅFIGURE 5 Two-channel record and playback system from Averna.

23.055

23.050

23.045

23.040

23.035

23.030

23.025

Latit

ude

(deg

rees

)

(a)

0 50 100 150 200 250 300 350 400 450 500 550 600Time (seconds)

Trial 1

Trial 2

Trial 3

Trial 4

Trial 5

Trial 6

Trial 7

Trial 8

Trial 9

Trial 10

114.390

114.380

114.370

114.360

114.350

114.340

Long

itude

(de

gree

s)

(b)

0 50 100 150 200 250 300 350 400 450 500 550 600Time (seconds)

Trial 1

Trial 2

Trial 3

Trial 4

Trial 5

Trial 6

Trial 7

Trial 8

Trial 9

Trial 10

114.385

114.375

114.365

114.355

114.345

ÅFIGURE 6 Receiver latitude (a) and longitude (b) over a four-min-ute span



development environment, one can parse all sentences to re-turn satellite and position-fi x information.

For practical testing purposes, GPS dilution of precision and active satellites (GSA), GPS satellites in view (GSV), course over ground and ground speed (VTG), and GPS fi x data (GGA) sentences are the most useful. More specifi cally, one can use information from the GSA sentence to determine whether the receiver has achieved a position fi x and is used in time-to-fi rst-fi x measurements. When performing sensitivity measurements in this example, the GSV sentence was used to return carrier-to-noise-density ratios (C/N0) for each satellite being tracked. In addition, the VTG sentence allows us to observe the velocity of the receiver. Finally, the GGA sentence provides the receiver’s precise position by returning latitude and longitude in-formation. See the references in Further Reading for in-depth information on the NMEA 0183 protocol.

Using the receiver’s reported latitude and longitude information, we are able to test its ability to report a repeatable posi-tion when the recorded signal is played back to the receiver. In this experiment, we tracked the receiver position over 10 minutes. For the best results, the com-mand interface of the receiver should be tightly synchronized with the start trig-ger of the RF signal generator. Th e re-sults in FIGURE 6 show that the RF vec-tor signal generator in this experiment was synchronized with the GPS receiver by using the data line of the serial com-munications (COM) port (RxD, pin 2) as a start trigger. Using this syn-chronization method, the vector signal generator and GPS receiver were syn-chronized to within one clock cycle of the VSG’s arbitrary waveform generator (100 MS/s). Th us, the maximum skew should be limited to 10 microseconds. Given our receiver’s maximum velocity of 15 meters per second (our maximum speed on the drive test), we can deter-mine that the maximum error induced by clock off set of the signal generator is 10 microseconds � 15 meters per second, or 0.15 millimeters.

Using the confi guration described above, one is able to report the receiv-er’s latitude and longitude over time, as

shown in Figure 6.As the data from Figure 6 illustrate, a recorded test-drive

signal reports static, position, and velocity information. In addition, one can observe that this information is relatively repeatable from one trial to the next, as evidenced by the dif-fi culty in graphically observing each individual trace. To bet-ter characterize the deviation between each trace, one can also compute the standard deviation between each sample in the

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waveforms. FIGURE 7 illustrates the standard deviation between each of the 10 trials, calculated for every one-second interval, versus time.

When observing the horizontal standard deviation, it is in-teresting to note that the standard deviation appears to rapidly increase at time � 120 seconds. To investigate this phenom-enon further, we can plot the total horizontal standard devia-tion against the receiver’s velocity and a proxy for C/N0. In this case, we simply averaged the C/N0 values for the four highest satellites reported by the receiver. Since four satellites are re-quired to achieve a three-dimensional position fi x, our assump-tion was that position accuracy would closely correlate with the signal strength of these important satellite signals.

One simple method to evaluate the horizontal repeatability of the receiver position versus time is to calculate the standard deviation on a per-sample basis of each recorded latitude and longitude (in degrees). Once the standard deviation is mea-sured in degrees, we can roughly convert this to meters with the following equation:

Deviation (meters) = LatSTDEV ×111325m( )2 +(LonSTDEV ×111325m × cos

Lat × π180

⎛⎝⎜

⎞⎠⎟

⎛⎝⎜

⎞⎠⎟

2 ⎞

⎠⎟

0.5

(8)Note that Equation 8 represents a highly simplifi ed error

calculation method, which assumes that the Earth is a perfect

sphere. For a more precise calculation of repeatability, the geo-desic formula (which presumes that the Earth is ellipsoidal) should be used. In our simple experiment, the goal is merely to correlate repeatability with other factors that we can measure from the receiver. FIGURE 8 illustrates the standard deviation of horizontal position repeatability over 10 trials and at one-second time intervals.

As one can observe in Figure 8, the peak horizontal error (measured by standard deviation) occurring at time � 120 seconds is directly correlated with satellite C/N0 and not corre-lated with receiver velocity. At this sample, the standard devia-tion is nearly 2 meters while it is less than 1 meter during most other times. Concurrently, the top four C/N0 averages drop from nearly 45 dB-Hz to 41 dB-Hz.

Th e exercise above illustrates not only the eff ect of C/N0 on position accuracy but also the types of analysis that one can conduct using recorded GPS data. For this experiment, the drive recording of the GPS signal was conducted in Huizhou, China (a city north of Shenzhen), but the actual receiver was tested at a later date in Austin, Texas.

ConclusionIn this article, we’ve illustrated how to use commercially avail-able off-the-shelf products to record GPS signals with an RF recorder, and then play the signal back to a receiver. As the results illustrate, recorded GPS signals can be used to measure a wide range of receiver characteristics. Not only can receiver designers use these test techniques to better prototype a receiv-er baseband processor, but also to measure system-level perfor-mance such as position repeatability.

Manufacturers The tests discussed in this article used a National Instruments (www.ni.com) PXIe-5663E, 6.6 GHz, RF signal analyzer; a National Instruments PXI-5690, 100 kHz to 3 GHz, two-channel programmable amplifi er and attenuator; a National Instruments PXIe-5672, 2.7 GHz, RF vector signal generator with quadrature digital upconversion; a 320 GB USB Passporthard drive from Western Digital Corp. (www.wdc.com); a Na-tional Instruments PXI-4110 programmable, triple-output, precision DC power supply; and a ZX85-12G-S+ bias tee man-ufactured by Mini-Circuits (www.minicircuits.com). The article also mentioned the RP-3200 2-channel record and playback system manufactured by Averna (www.averna.com), which in-corporates National Instruments modules. �

DAVID HALL is an RF product manager for National Instruments. He holds a bachelor’s of science with honors in computer engineering from Pennsylvania State University.

0 50 100 150 200 250 300 350 400 450 500 550 600Time (seconds)

1.50

1.25

1.00

0.75

0.50

0.25

0.00

Sta

ndar

d de

viat

ion

(met

ers)

LatitudeLongitude

ÅFIGURE 7 Standard deviation of both latitude and longitude over time

0 50 100 150 200 250 300 350 400 450 500 550 600Time (seconds)

50

45

40

35

30

25

20

15

10

5

0

Standard deviation (meters)

Mean velocity (meters/second)Average C/N0 (dB-Hz)

ÅFIGURE 8 Correlation of position accuracy and C/N0.

Further ReadingFor references related to this article, go to gpsworld.com and click on Richard

Langley’s Innovation under Inside GPS World in the left-hand navigation bar.

MORE ONLINE


Road | TRANSPORTATION

V2X can include applications based on communications between any two or more entities on the road. Of all the potential V2X applications, V2V applications

probably lead the way in terms of maturity of prototype development and test efforts. General Motors (GM) demonstrated the first working prototype V2V system in 2005. Information on further industry collaborative efforts in V2V system developments can be found at the U.S. Department of Transportation’s (DOT’s) IntelliDrive website (www.intellidriveusa.org). While a multitude of applications could be developed based on V2I capability, most of the related system prototype development efforts have taken place under the DOT’s Cooperative Intersection Collision Avoidance (CICAS) program (www.its.dot.gov/cicas).

Accuracy RequirementsIn terms of positioning accuracy requirements, Vehicle Safety Communications-Applications (VSC-A) prototype system ca-pabilities as well as all V2X applications can be classifi ed as:� Which Road. In this case, accuracy is only required to the extent of identifying the road traveled. For instance, if a vehicle is in a service road parallel to a freeway, knowing that it is on

the service road and not on the freeway is sufficient. The need of a typical vehicle navigation device is another good example of this requirement category. The typical accuracy requirement for this case is better than 5 meters. However, this could be a relative accuracy requirement for certain applications. For in-stance, in a V2V scenario, one vehicle may only need to know if the other is on the same road or not, while in the absolute sense both vehicles could be in error by more than 5 meters. For V2I applications, however, this becomes an absolute accu-racy requirement, as the infrastructure is always mapped and identified with respect to a global coordinate frame. � Which Lane. This accuracy level enables applications to identify other entities with lane level resolution. The typical requirement is 1.5 meters or better, which approximately cor-responds to half of a lane width. A blind-spot advisor is a good example that requires this accuracy. � Where-in-Lane.This accuracy level enables the relative positioning of entities to better than 1 meter. Further refine-ments of blind-spot advisor-like applications are examples.

Availability RequirementsGNSS as a line-of-sight technology has obvious limitations in

Chaminda Basnayake, Tom Williams, Paul Alves, and Gérard Lachapelle

Communication-enabled vehicle safety has the potential to change transportation’s future, particularly vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I), collectively represented as V2X. An automakers’ consortium conducted extensive field trials to determine GNSS service availability and accuracy for the V2X challenge.

Å DRIVING ENVIRONMENTS encountered in testing. Clockwise from top left: deep urban, urban thruway, local roads, mountains.

CanCan GNSSGNSSDrive Drive V2XV2X??


TRANSPORTATION | Road


certain environments, and these limita-tions are well understood by the GNSS community. The focus of this study was to understand the limitations associated with a GNSS-only V2X solution such that requirements for augmentation technologies can be defi ned. Therefore, no availability requirements were set for the system; estimating availability of a GNSS-only solution was the goal.

Why So Complicated? At first glance, what needs to be done is straightforward; all V2X-capable entities need to be aware of each other’s positions. Hence, if all entities transmit their own location with respect to the same coordinate system, the problem is solved. Unfortunately, it’s not that simple.

Designing the system so that hundreds of entities, potentially using all sorts of GNSS software and hardware, can work together presents a significant challenge. This includes keeping backward compatibility way out into the future.

Even within the same receiver make and type, inclusion of a particular satellite in the solution of one vehicle can significantly affect the solution difference between vehicles. Inclusion of SBAS also contributes as a differentiator. In a V2X scenario, out of two adjacent vehicles, one vehicle may use SBAS while the other may not, due to hardware configuration or visibility. If none of the above situations occurred and everything else were ideal, transmitting just the current horizontal position of a V2X entity over-the-air (OTA) would be sufficient to do everything needed.

V2X thus requires a positioning system architecture that minimizes the impact of these complications and many other

potential compatibility issues. Major system design considerations include:

Performance Requirements. The system must provide relative positioning accuracy that fits Which Road, Which Lane, or Where-in-Lane category and should identify the solution quality. For instance, a vehicle on a freeway with relatively open sky view may function in the Which Lane mode and may transition to Which Road mode as it enters an urban area with sky visibility limitations.

Deployment Constraints. The system must be affordable for automotive applications. This may also include considerations such as antenna placement, processing resource requirements, and power requirements.

Bandwidth Constraints. The volume of data transmission constitutes a major consideration for OTA communications. W h i l e s o m e m e t h o d s m a n a g e communication range and frequency as a way of optimally using the communication channels, keeping the OTA data volume to a minimum by design was a goal.

Study GoalsThis study investigated the performance of two relative positioning methods: DPOS, a method of using the difference in position reported by two entities to calculate the 3D separation between the points; and real-time kinematic (RTK). While there are many other possible rela-tive positioning methods, these two were selected as they collectively represent the most desirable availability and accuracy performance. In DPOS, vehicle coordi-nates are transmitted between vehicles in order for position differences between vehicles to be derived at each vehicle. In

RTK, raw code and carrier-phase data is transmitted between vehicles, and the in-ter-vehicle position differences are calcu-lated using RTK software in either fi xed or fl oat carrier-phase ambiguity mode at each vehicle. The RTK method is more intensive both from a data transmission and computational aspect, but retains only common satellites in the solution, eliminating the problem described earli-er. Its use of carrier-phase measurements also makes it more accurate.

The study included two GPS receiver types. The first, a single-frequency L1 automotive-grade receiver, is identified as Type B receiver in this study. The second, identified as Type A, was of a higher quality with proprietary multipath mitigation technologies. Both receivers were capable of using WAAS support. Receiver B also allowed the user to reject selected satellites from its solution. These two devices were selected as they were capable of supporting both processing methods, and represent on the one hand an existing automotive-grade receiver, and on the other hand one that is expected to be a good representation of a product with technologies available for automotive deployment a few years from now.

Specific study goals were:� Accuracy performance of DPOS

and RTK methods when all vehicles use same GPS receiver type.

� Same when a receiver type or a receiver configuration mix is used.

� Dependency of the accuracy perfor-mance on the driving environment.

� Solution availability with same receiver and mix receiver combina-tions.

� Implications of non-continuous V2I coverage.

Prototype SystemThe system prototype (FIGURE 1) used for the study was a replica of the proto-type relative positioning system imple-mented in the VSC-A project. It consists of a dedicated short-range communi-catin (DSRC) interface with a DSRC radio, a GPS receiver/relative position-ing module, and a sensor data handler.

Å FIGURE 1 VSC-A prototype relative positioning system.



In operation, a vehicle generates its own location information and GPS raw data in RTCM format and shares this data with other vehicles. OTA messaging was done using the SAE J2735 messages set with GPS raw data in RTCM format attached as optional data. As shown in Figure 1, RTCM v3 1002 messages were used to exchange VSC-A data. The system was also capable of using RTCM v3 messages 1001 & 1005 for V2I operation. The DPOS relative positioning logic was implemented in the sensor data handler, while the RTK implementation was done in a separate relative positioning module. This module takes in local and remote 1002 messages and outputs RTK data to the sensor data handler. Applications could access both RTK and DPOS relative positioning information from the sensor data handler.

Vehicle Setup. Two vehicles were used for the V2X data collection. Four different GPS L1-only test receiver types were installed on each vehicle:� AW: high-quality receiver using

WAAS corrections.� BW: high-sensitivity automotive-

grade receiver with WAAS ranging and corrections enabled.

� BNW: high-sensitivity automotive-grade receiver with WAAS ranging and corrections disabled.

� B24W: high-sensitivity automotive-grade receiver using a maximum of the four primary satellites in each of the six planes (minimum guaran-teed constellation) and with WAAS ranging and corrections enabled. As shown in FIGURE 2, the AW and B

type receivers were connected to different GNSS antennas. These antennas were mounted on roof-racks attached to the vehicles (see PHOTO). The patch antenna for the Type B receivers was mounted on an aluminum-topped wooden pedestal to bring it to approximately the same height as that used by the AW receivers, to provide a ground plane and to prevent shading from other equipment on the roof-racks. The spacing between the antennas was accounted for in all analysis.

Figure 2 also shows that only three

of the four test receivers, AW, BW, and BNW, were connected to the computer that ran the RTK software. This computer calculated the inter-vehicle vector (IVV) using information exchanged over the DSRC radio link in real time. The vehicles each had a designated base relative to which the IVV was calculated; for Vehicle 1 it was BW and for Vehicle 2 it was AW. Thus the computer on each vehicle calculated three instances of the IVV, for example, the computer on Vehicle 1 calculated BW

1–BW

2, BW

1–BNW

2, and BW

1–AW

2

(where Ri denotes the receiver of type R

on vehicle i).Transmission and reception of data

between the two vehicles required for the IVV RTK calculations were achieved using wave radio modules with two magnetically mounted 802.11p antennas on each vehicle for redundancy. During testing, Vehicle 1 generally followed Vehicle 2. To minimize potential interference of roof-mounted instruments on between-vehicle communications, the antennas on Vehicle 1 were located close to the front of the roof, while those on Vehicle 2 were located close to the rear of the roof. In each case, 15 centimeters of roof space were left to provide ground planes for the antennas.

We used the single-point navigation solutions logged from each test receiver

to calculate the IVV for each receiver combination using the DPOS method in post-processing. No real-time data transfer between the vehicles was used for this method.

Reference values of the IVV were calculated in post-processing using both geodetic grade GPS/GLONASS L1/L2 receivers and GPS/INS integrated systems in differential mode. Both were connected to the antenna used by the AW receiver. Differential GPS calculations were enabled by using stationary receivers with antennas at precisely known WGS84 locations on top of a building at the University of Calgary.

ÅFIGURE 2 High-level V2V hardware setup on each of the two test vehicles.

ÅTWO STUDY VEHICLES with antennas attached to the roof-racks.



Test Scenarios V2V data was collected in and around the city of Calgary in August 2009. In the majority of the tests, Vehicle 1 fol-lowed Vehicle 2 with a separation of less than 300 meters, the stated effec-tive range of the DSRC link. For most tests the inter-vehicle separation was between 30 and 150 meters. Some driv-ing environments forced modifi cations of the default behavior; for example, on highways, vehicles moved in between the two test vehicles, necessitating lane changes. Approximately 52 hours of data was collected over 12 days. After rejecting data due to various faults such as reference-system malfunction, more than 45 hours of data remained.

Data was collected in the seven test environments listed in TABLE 1. These environments were selected in accordance with Federal Highway Administration descriptions. Each environment provided different challenges for GNSS-based positioning. Obviously the deep urban environment was challenging because the reduced number of visible satellites and the large amount of multipath meant that navigation solutions were both rare and of poor quality. As another example, the mountain environment was interesting because often almost half the sky was occluded by trees on the mountain side, leading to an asymmetrical visible GPS satellite constellation with the associated solution degradation. The photos at the beginning of this article show selected driving environments encountered during testing.

V2V Solution Accuracy. Positioning accuracy of the individual receiver was first investigated to estimate the V2V relative positioning accuracy when using the DPOS method. This was done for the entire dataset.

FIGURE 3A shows a representative freeway dataset to illustrate overall trends: the absolute 2D mean position errors observed from all eight GPS receivers used in both vehicles. The first set of four receivers shown were the AW, BW, BNW, B24W receivers in the first vehicle (V1), and the second set of receivers were the

same type in the second vehicle (V2). As a general trend, Type A receivers provided better absolute accuracy meeting the Which Lane accuracy, whereas the Type B receivers provided Which Road accuracy. Also, the use of WAAS with receiver Type B has yielded some absolute accuracy improvement. Limiting the constellation to 24 (B24W) did not significantly degrade accuracy in this case.

As a second step, V2V relative accuracy when the same receiver type was used was estimated, and the mean errors are shown in FIGURE 3B. Based on the mean error for each pair, all four receiver pairs were able to provide Where-in-Lane relative position accuracy. The geodetic grade Type A receiver pair (AW–AW) yields the best relative accuracy at around 0.5 meters relative 2D error. In comparison

38

ÅTABLE 1 Description of driving environments used in V2V tests.

ÅFIGURE 3A (top) Individual receiver absolute accuracy; 3B (mid) Relative accuracy with same receiver type; 3C (bottom) Relative accuracy with receiver/configuration mix.

Environment Description Mask Angle Speed & Dynamics % of Data

Local RoadsSuburban residential streets, occasional tree canopy.

10° to 90° depending on trees and neighbor-hood.

Max: 25 mph. Frequent starts, stops, and corners.

14.4

Urban ThruwayMajor multilane roads with nearly constant 3–4 storey buildings.

Around 20°.Max: 50 mph. Mainly free-flowing, occa-sional traffic jam.

21.8

Rural ThruwayMultilane road with occasional 3–4 storey buildings.

From 5° to 20°.Max: 50 mph.Free-flowing and mainly straight.

19.2

Major RoadsSimilar to urban and rural thruways with lower speed limit.

5° (rural) to 20° (urban)Max: 40 mph.Frequent starts and stops, mainly straight.

18.1

FreewayFreeways with open-sky view and occasional overpass.

5° or less. Max: 60 mph. Free-flowing, mainly straight.

20.1

MountainsFreeways on mountain sides.

20° to 60° depending on trees.

Max: 60 mph. Frequent changes in direction.

2.5

Deep UrbanRoads in downtown core flanked by highrises.

Generally 20° to 40°, as high as 80°.

Max: 25 mph. Frequent starts and stops

3.7



with the mean absolute errors, the V2V relative accuracy is greatly improved as a result of cancellation of correlated errors, indicating a high degree of correlation of absolute errors in receivers under these test conditions.

The relative accuracy with mixed receiver types or configurations was also estimated. With respect to receiver type mixes, the Type A receiver from vehicle 1 was used with the three Type B receivers in vehicle 2, yielding three combinations as AW–BW, AW–BNW, and AW–B24W. Mean error statistics for these three combinations and the combination of BW from vehicle 1 and B24W from the second vehicle are shown in FIGURE 3C. In comparison to the same type receiver pairing, this shows much larger mean errors. For instance, for all AW receiver mixes, the mean relative error is around 2 meters. Therefore, it is fair to conclude that error characteristics and modeling in the navigation solutions in receiver A and B are type-dependent, and they may not be compatible when a receiver mix is used. The BW–B24W combination does not show a significant increased mean error, indicating that the constellation difference in this test was not significant enough to result in an increased relative positioning error.

V2V Solution Availability Availability statistics were generated for all accuracy categories (Which Road, Which Lane). At a more abstract level, solu-tion availability statistics were also calculated for the DPOS and RTK methods. RTK solutions were defi ned as available whenever the software yielded a solution for that particular ep-och. Data gaps in the RTK method could be caused by either communication failure due to, for example, a large truck enter-ing the line of sight between vehicles, or one vehicle disappear-ing around a corner, or because insuffi cient observations from common satellites were available at the two vehicles. DPOS solutions, calculated in post-processing, were defi ned to be available whenever both receivers had observations from four or more satellites and were therefore able to calculate the neces-

sary independent position solutions. While the two defi nitions of availability are not quite congruous, because only that for the RTK includes the possibility of communication failure, comparison of logs of data transmitted between the vehicles showed that out of approximately 45 hours of data, only 0.22 percent of missing RTK solutions could be attributed to failure of the DSRC link.

FIGURE 4 plots the distribution of GPS service outages observed by AW and BW receivers in individual vehicles in all of the test environments including deep urban. Here, as described for the DPOS method, an outage for a single receiver is identified on an epoch basis whenever the receiver has observations from less than four satellites. The total driving time included in this dataset is 45 hours and 4 minutes for each receiver. Figure 4 [deep urban] shows the same statistics for deep urban environment driving only, and this contains 1 hour and 40 minutes of driving for each receiver. The latter was selected specifically as this environment contained the most challenging conditions.

An important conclusion based on this data is that more than 98 percent of the individual vehicle-level service outages in the entire study lasted less than 30 seconds using any one of the receiver types. For the deep urban environment, 93 percent of the outages lasted less than 30 seconds. However, when using the high-sensitivity enabled Type B receivers, 100 percent of the outages lasted less than 5 seconds. No significant outage difference is seen between the observations from the same receiver type in the two vehicles.

GPS service availability for V2V applications was calculated using two approaches for the two relative positioning methods. For the DPOS method, individual vehicle service availabilities were time-synchronized in post-mission, and V2V DPOS solution availability was estimated. FIGURE 5 compares V2V solution outages using both receiver types and both relative positioning methods.

The DPOS method yields better solution availability statistics than RTK. With both receiver types, more than 95 percent of

Å FIGURE 4 Distribution of GPS service outages for individual vehicles.

Å FIGURE 5 Distribution of GPS service outages for V2V applications.



DPOS solution outages are less than 10 seconds. With the RTK method, relatively longer outages were observed, especially for Type B receivers. With Type A receivers, the difference is only significant for outages shorter than 30 seconds. For Type B receivers, larger percentages of longer RTK outages were observed; this can be potentially attributed to poor carrier-phase tracking loop performance of these receivers and the impact on RTK.

Using GNSS Data We anticipated performance issues aris-ing from receiver type and confi guration incompatibilities going into the proto-type development effort. We identifi ed use of raw GPS measurements instead of the DPOS method as one method to overcome this limitation, as the dif-ferencing techniques with measurement data guarantees correlated error cancel-lation. This was one reason to include the RTK capability in the prototype sys-tem. Therefore, confi rming the fact that use of raw measurements eliminates the receiver type and confi guration-related incompatibilities was a major goal of the study.

As discussed earlier, V2V relative position solutions using RTK were logged in real time as a part of the test setup. We compared these real-time RTK solutions and the DPOS solutions estimated in post-mission for all datasets. FIGURE 6 shows three cumulative probability distribution (CDF) plots generated using RTK and DPOS accuracy data from a freeway test dataset. The first CDF plot (left) shows the comparison of accuracy when both

vehicles use Type A receivers with RTK and DPOS methods. The second CDF plot (center) shows the same CDFs when both vehicles use the Type B receivers. The third shows the DPOS and RTK accuracy CDFs when vehicle 1 uses Type A receiver and the other uses Type B receiver.

Figure 6 demonstrates that if higher quality GPS receivers similar to Type A are used in both vehicles, both RTK and DPOS methods would provide a solution of better than Which Lane accuracy more than 90 percent of the time. However, if Type B receivers are used, a solution with similar accuracy will only be available 60 percent of the time if the DPOS method is used for relative positioning of the vehicles. If the RTK method is used, this availability can be increased up to 90 percent.

The performance difference between the two methods becomes even more prominent when the two vehicles use a mix of receiver types. In the right-most CDF of Figure 6, a solution with Which Lane accuracy is only available 30 percent of the time if DPOS method is used with the mixed receiver configuration. The RTK solution availability still remains around 90 percent even with the mixed configuration. This confirms that use of measurement data eliminates some of the limitations associated with the DPOS method.

Compari son of only the RTK performance between all three CDFs in Figure 6 shows that RTK V2V performance is only limited by the worst-performing receiver in the receiver combination. Out of the three CDFs, the middle (both vehicles using Type B) and the right (Type A and B mix) CDFs have

almost identical RTK performance curves. Given that the RTK curve with both using Type A receivers shows much better performance, it is fair to conclude that in the mixed-receiver case, the RTK curve is limited by the performance of the Type B receiver. Figure 6 also shows that at Which Road accuracy, all receiver combinations and both processing methods yield almost identical performance.

Other Approaches Given that carrier-phase measurements are subject to cycle slips in some road environments, we ran a test using code measurements only in relative mode, using selected data sets collected on a mountainous highway. Only common satellites were used. Given that code measurements are not affected by a loss of phase lock, such a solution is more robust, but is subject to code noise and multipath. The RMS horizontal posi-tion differences between these solutions and the reference inter-vehicle separa-tions were 25 centimeters and 1 meter for receiver Types A and B, respectively. Both receiver types meet the Where-in-Lane requirement in this test. Type A, with its low code noise and excellent code multipath-reduction capability, has a clear advantage.

Such an approach would represent a compromise between the DPOS and RTK approaches. Its advantage over the RTK approach is a lower data transmission-rate requirement, while that over the DPOS approach is the use of common satellites only. The latter is quite significant, since low-elevation satellites contribute the

Å FIGURE 6 Comparison of V2V solutions using RTK and DPOS methods.



most to horizontal position solutions, but their measurements are affected more by atmospheric transmission errors that are most effectively removed in differential mode on a satellite-by-satellite basis.

V2V Operation with V2IWhile infrastructure support can almost always improve the performance of other V2X applications, it can pose a challenge for positioning when such coverage is not continuous. The complication arises as a result of vehicles transitioning in and out of V2I coverage areas. V2I systems are highly likely to include GNSS augmen-tation capability so that vehicles within a coverage area benefi t from better posi-tioning capability. However, when vehi-cles transition from standard (V2V) op-eration mode to a V2I enhanced mode, some effects in the vehicle position do-main can pose potential challenges for DPOS-based V2V.

The field study included test scenarios with limited V2I coverage in different driving environments: all of those described above with the exceptions of deep urban and mountains. In deployment, the infrastructure points (IPs) would broadcast aiding information to the vehicles within their coverage area, allowing real-time calculations. In the field study, in which the role of the IP was filled by a stationary high-grade receiver with a tripod-mounted antenna, all V2I estimates of the IVV were calculated using post-processing. Further, V2I estimates of the IVV were only calculated when at least one of the vehicles was within the coverage area of

the IP, here chosen to be a circle of radius 300 meters centered at the IP. This range was chosen since it is the nominal effective range of the DSRC link.

The location of the IP, that is, the phase center of the stationary antenna, was determined using commercial RTK network software with additional stations at precise locations on the rooftop of a building at the University of Calgary. The estimated accuracy of this position was 5 millimeters (1 sigma). The distances of the vehicles from the IP, used to indicate when the vehicles transitioned into and out of the IP coverage area, were determined using the GPS/INS reference trajectories. In post-processing, once a vehicle was identified as having entered the IP coverage area, commercial RTK software was used to estimate the position of the vehicle, using the IP as base and each of the test receivers on that vehicle as rovers. The IVV was then calculated using the difference of the positions of the two vehicles. Thus, the V2I estimate of the IVV was determined using what is essentially the DPOS method with stationary base RTK-indicated vehicular positions, instead of the less accurate single-point GPS position solutions. When only one vehicle was within the coverage area, single-point solutions were used for the distal vehicle, resulting in a solution called V2I-S.

FIGURE 7 shows two sets of CDFs generated to i l lus t ra te the V2V positioning accuracy with V2I capability. The left plot corresponds to AW–AW receiver combination, and the right plot corresponds to the BW–BW combination.

Each plot includes four curves. One pair of curves shows the V2V positioning accuracy without V2I, which includes performance when using the DPOS method (green) and another when using RTK (blue). The second pair shows the accuracy of the V2I and V2I-S estimates.

The most striking observation from Figure 7 is the separation of the V2I-S case from others for both receiver combinations (purple). It shows much worse positioning accuracy compared to the other three curves. For instance, using a BW–BW pair, the system will meet the Which Lane accuracy requirement around 80 percent of the time for either DPOS or RTK V2V without V2I support. However, when V2I coverage is available to only one vehicle, the V2I-S case, the accuracy requirement is only met at 40 percent confi dence.

Thus, system accuracy performance degrades when vehicles are operating in DPOS mode and are transitioning in and out of the V2I zones. This is because the V2I-S estimate is the difference of an accurate position solution for the vehicle within the coverage zone, and a potentially inaccurate single-point solution for the one outside the coverage zone. The benefi cial cancellation of similar errors that occurs for DPOS estimates (using similar receivers and with common satellite observations) does not occur for V2I-S.

Potential solutions to this problem include using a V2I method of IVV calculation that is not dependent on the estimated position alone (that is, use RTK or other measurement-based methods as opposed to DPOS), or using a position-mode indicator with the DPOS mode such that a DPOS-based V2V solution is only generated when both vehicles are operating in the same mode (that is, V2I). However, the latter does not provide a remedy for the complications when the two vehicles are operating in two different modes. One could also consider a variation of the latter method whereby a V2I-augmented position and a non-augmented position is maintained by each vehicle, such that one of them could be used to generated a mode-matched DPOS V2V solution for a given sender.

Å FIGURE 7 Average relative positioning accuracy as a function of V2I positioning modes (orange V2I; green DPOS; blue RTK; purple V2I-S).



RecommendationsThese extensive trials provided valuable data demonstrating technical challeng-es associated with V2X positioning. � Error characteristics and modeling in the navigation solutions in receivers A and B are type-dependent, and they may not be compatible when a receiver mix is used with the DPOS mode. This is very likely to be the case for many other commercial receivers. Therefore, it is important to develop receiver hard-ware and software minimum-perfor-mance standards that define acceptable performance for measurement quality, satellite tracking and selection criteria, reliability estimates, navigation-solution parameters, and other such indicators. � Findings with RTK confirm the fact that use of measurement data elimi-nates some of the limitations associated with the DPOS method. While RTK is the most demanding raw data-based method in terms of processing require-

ments and OTA data needs, the study also conducted limited investigation on other methods that use raw code data and are less resource-intensive, and at the same time better performing than DPOS. Such an approach would repre-sent a compromise between the DPOS and RTK approaches. � An important conclusion based on this data is that more than 98 percent of the individual vehicle-level service out-ages in the entire study lasted less than 30 seconds using any one of the receiver types. For the deep urban environment, 93 percent of the outages were less than 30 seconds. These statistics are useful for future research on suitable GNSS augmentation methods. � System accuracy performance de-grades when vehicles operate in DPOS mode and transition in and out of the V2I zones. Potential solutions should be incorporated into the systems to take care of these limitations. �

AcknowledgmentsThe authors thank the Crash Avoidance Metrics Partnership Vehicle Safety Com-munications-Applications team, in par-ticular the Vehicle Positioning Technol-ogy Development team, for input. This work was conducted as a part of a CAMP VSC-A project under a cooperative agree-ment with the U.S. DOT.

CHAMINDA BASNYAKE is a senior research engi-neer at General Motors Global Research and Development and GNSS technology expert for GM OnStar. He leads GNSS-based vehicle navigation technology R&D efforts at GM and holds a Ph.D. in geomatics engineering from the University of Calgary. TOM WILLIAMS is a postdoctoral researcher in the PLAN group in the Department of Geomatics Engineering at the University of Calgary.PAUL ALVES is a Calgary-based geomatics consul-tant specializing in RTK. He obtained his doc-torate from the University of Calgary.GERARD LACHAPELLE holds an iCORE/CRC Chair in Wireless Location and heads the PLAN Group in the Department of Geomatics Engineering at the University of Calgary.

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SURVEY | Mapping


A irborne light detection and ranging (LiDAR) surveys are among the most advanced

means of producing high-resolution, ac-curate surface elevation models used for many applications in surveying and civil engineering. Precise geolocation and orientation (or georeferencing) of the LiDAR instrument with a combination of on-board GNSS and inertial sensors at the times when the measurements are made provides the key to high-quality elevation products.

Th e usual practice deploys reference GPS/GNSS land receivers in the area where the aircraft will be fl ying, to ob-tain a precise trajectory by short-base-line diff erential GNSS techniques. Th is could mean installing and operating re-ceivers at many sites during a fl ight mis-sion if the area surveyed is a large one.

We have tried a diff erent approach: using as reference receivers those of a sparse network of Continuously Operat-ing Reference Stations (CORS) in New South Wales known as CORSnet-NSW, and a wide-area diff erential GPS tech-nique for obtaining the aircraft trajec-tory with sub-decimeter accuracy even with baseline lengths of several hundred kilometers. Th is may be comparable in precision and accuracy to the short-base-line method, but without the cost and

logistical complications. Th is opens up a new level of operational capability, al-lowing fl exibility for weather conditions and priority response applications.

Th e tests described here were orga-nized and conducted by the NSW gov-ernment’s Land and Property Manage-ment Authority, in collaboration with the University of New South Wales, in June 2009. CORSnet-NSW consists, at this writing, of 46 stations and by 2012 will provide statewide GNSS position-ing infrastructure across NSW with a planned 70 stations in operation.

Precise Wide-Area PositioningWe used a technique for long-baseline differential, off-line positioning, able to deliver centimeter precision for fi xed re-ceivers and sub-decimeter precision for moving receivers. This choice was dic-tated by three considerations: � The intended application was the

geolocation of the data of an airborne scanning LiDAR sensor to be used in the generation of high-accuracy digi-tal elevation models (DEM).

� Off-line processing, where all the GNSS data collected during the flight are available for processing and (as in this case) there is no need for immediate results, is intrinsically more reliable than real-time process-

ing, where the data are available only up to the present epoch, and accurate results must be obtained right away, with no chance for a second try.

� Differential processing makes it pos-sible to resolve the carrier-phase ambiguities using well-understood methods.Technique. It is common practice in

airborne LiDAR surveys to use GNSS both to position the instrument precisely, and to assist an inertial navigation system (INS) to obtain the orientation of the aircraft in space, as both position and orientation are needed to interpret the data properly. FIGURE 1 illustrates the relationship between the sensors used for airborne LiDAR surveys. The aircraft uses a GNSS antenna combined with an INS to georeference its trajectory. The bore-sight calibration process aligns the individual sensor orientations and standardizes the range measurements. However, if the survey is to achieve the now-expected high level of vertical accuracy (�15 centimeters, 1 sigma), then the position of the GNSS/INS-derived aircraft trajectory for each laser swath must be determined with a relative precision in the order of just a few centimeters. This is achieved via differential GNSS post-processing of the kinematic airborne data together with static observations collected on precisely

Oscar L. Colombo, Shane Brunker, Glenn Jones, Volker Janssen, and Chris Rizos

The use of a precise wide-area positioning technique for airborne trajectory solutions for LiDAR surveys provides both relative and absolute accuracies similar to those derived from using a local GNSS reference station.

SURVEY | Mapping

Sparse Network Wide-Area, Sub-Decimeter Positioning for Airborne LiDAR Surveys


Mapping | SURVEY

surveyed ground reference stations. The GNSS positions are then blended with high-frequency measurements taken by the onboard INS to produce the final trajectory and reference orientations.

To such ends, the aircraft trajectory is usually determined by short-baseline diff erential GNSS, with ground receivers de-ployed near the intended fl ight path of the aircraft. In this way it is possible to use GNSS data analysis techniques that are both precise and quite straightforward to implement in soft-ware. Th e simplicity of these techniques is possible because, in short-baseline diff erential solutions, the data of the aircraft receiver and any nearby network receivers have much the same systematic errors (due to such things as satellite ephemerides errors, transmission delays, and so on) that cancel out — or nearly so — when their observations are diff erenced between them. Th is also makes it possible to resolve quickly and reliably the cycle ambiguities in the observed carrier phase, the most precise type of GNSS data, overcoming one of the main ob-stacles to obtaining good results. Furthermore, it is possible to get such results with single-frequency receivers, as ionospheric delay is one of the systematic eff ects that can be largely can-celed out.

In wide-area solutions, those cancellations are not complete enough to ignore the systematic data errors, and they have to be included in the form of additional unknown parameters in the observation equations. Also, it is necessary to account for the ionospheric delays using dual-frequency data, which means using more expensive GNSS receivers and antennas.

Resolving the carrier-phase ambiguities is no longer straight-forward or assured. Th e standard way of dealing with the am-biguities is to include them as unknowns in the observation equations and adjust them along with the other unknowns: this is often referred to as “fl oating the ambiguities.” Fixing (or resolving) those ambiguities to their most likely integer values in a matter of seconds to a minute is possible on occa-sion, when the aircraft is within less than 20 kilometers from a ground receiver, or very precise corrections for the ionospheric delay are available; otherwise slower techniques, that require tens of minutes, may be used. It is also necessary to correct as well as possible such things as the neutral atmospheric delay of the GNSS radio signals, the movement of the “fi xed” stations due to plate tectonics, the solid earth tide using mathematical models, and, in the case of the tropospheric delay, estimating the error in the corrections made using a standard formula as an additional unknown per receiver.

Over the years all these diffi culties have been gradually dealt with more eff ectively, more effi ciently, more reliably and, from the user’s point of view, less painfully. Originally developed for the repeated determination of station positions to measure the slow tectonic deformations of the Earth’s crust, and to calcu-late precisely the orbit of Earth-observing satellites, these days, after nearly 30 years of steady progress, GNSS wide-area tech-niques and the corresponding software fi nd many applications in science, engineering, and navigation, and are becoming

widely used in remote sensing.Software. We used the Interferometric Translocation (IT)

wide-area positioning software developed by one of us for the long-baseline aircraft trajectory solutions and also to re-position in the IGS05 international reference frame some CORSnet-NSW stations, so their data could be used consistently in the diff erential wide-area solutions. Th ese stations were originally given in the Geocentric Datum of Australia (GDA94). For both purposes we used the precise fi nal GPS orbits computed and distributed by the IGS.

To validate the aircraft trajectories calculated with the wide-area method, we relied mainly on the quality of the LiDAR DEM results obtained with those trajectories. We also used commercial software to generate short-baseline diff erential solutions with receivers deployed near the intended aircraft fl ight-path, as is common practice in this type of survey, and compared them with the wide-area solutions (they turned out to be quite similar to short-baseline solutions obtained with the wide-area software).

Airborne TestsThis study has used data from two airborne LiDAR surveys conducted by the NSW Land and Property Management Au-thority (LPMA) in June 2009. The fi rst took place near the township of Glen Innes, and the second was a bore-sight cali-bration fl ight near the city of Bathurst. For both LiDAR sur-veys, the following data were acquired:� Aircraft trajectory, raw dual-frequency GPS (1 Hz) and

IMU data (200 Hz).� LiDAR (raw return data for each laser pulse).� GPS reference station data from local receivers and mul-

tiple CORSnet-NSW sites.Glen Innes Test. Th is operational LiDAR survey estab-

lished GND1 as the local reference station within the survey area. CORSnet-NSW data were collected for the test from GNSS receivers in Ballina (BALL), Grafton (GFTN), Nowra (NWRA), and Wagga Wagga (WGGA). FIGURE 2 shows the distribution of the reference stations and the fl ight runs.

Bathurst Test. Bathurst Airport is LPMA’s LiDAR calibra-

ÅFIGURE 1 Airborne LiDAR reference frame.

Mapping | SURVEY

SURVEY | Mapping


tion site and has various arrays of accurate ground checkpoints. AIR2, near the runway of the Bathurst airport, is the locally established GNSS reference station. CORSnet-NSW data were collected for the test from receivers in Ballina (BALL), Dub-bo (DBBO), Grafton (GFTN), Newcastle (NEWC), Nowra (NWRA), and Wagga Wagga (WGGA). FIGURE 3 shows refer-ence-station distribution and a schematic of the fl ight runs.

Effect on LiDAR DataRather than simply comparing aircraft trajectories, this study aimed to determine what effect the use of wide-area GNSS positioning has on the actual LiDAR point data and associated

elevation surfaces. In terms of the horizontal accuracy required for LiDAR surveys, initial tests showed that the differences be-tween the horizontal positions of various trajectories was neg-ligible; therefore, only the vertical component was considered in this analysis.

To quantify diff erences between LiDAR data generated from trajectories using various combinations of distant GNSS reference sites, we applied four types of analysis:� Comparison of trajectories — directly compare the

locally computed trajectory (assumed to be truth) with each wide-area derived trajectory.

� Relative LiDAR point comparison — compare the posi-tions for a sample of LiDAR ground points derived from the locally computed trajectory with those derived from each wide-area derived trajectory.

� DEM comparison — difference the raster surfaces derived from the locally computed trajectory and a wide-area derived trajectory to find the effect over a LiDAR run.

� Absolute LiDAR ground control comparison — com-pare the LiDAR derived surface from various trajectories to the surveyed ground control (Bathurst Calibration test site only). This also involves vertically shifting the result-ing surface so that its offset relative to the one used as control is zero, thus removing the effect of using different reference frames for the GNSS trajectories and the con-trol surface.

Trajectory ComparisonThe comparison between the locally determined and each wide-area derived trajectory was made along the entire trajec-tory for each fl ight. The importance of this step lies in the as-sumption that all LiDAR data are directly positioned from the trajectory and so any systematic effect in the trajectory should be refl ected on the ground. For each test site the locally derived solution is assumed to be “truth” with the vertical difference computed against wide-area solutions for each combination of reference stations used (TABLE 1).

The ”IT” Software� Runs under Windows, Unix, Linux, and FreeBSD.� Source code compatible with most Fortran compilers.� Follows the IERS 2003 conventions.� Available mainly for collaborative research purposes, with a

Free Software Foundation General Public License.Type of solutions:� Recursive, post-processing (Kalman filter + smoothing).� Kinematic and static.� Stop-and-go for rapid mobile surveys with pre-surveyed way-

points.� Differential, precise point positioning, mixed mode (precise

differential + point positioning).Data corrected for: Earth tide, neutral atmosphere radio signal

delays, carrier phase windup, and so on.Estimated parameters: � Receiver position in the IGS05 reference frame, with the

WGS84 reference ellipsoid, earth spin-rate, light speed, GM constant.

� Biases in ionosphere-free carrier-phase linear combination (“floated” ambiguities).

� Neutral zenith delay correction error.� Broadcast orbit errors (allows precise differential near-real

time solutions).� Integer ambiguity resolution available in differential mode,

with short baselines up to 20 kilometers (in minutes), and baselines of unlimited length (in tens of minutes — or just minutes, with a precise ionosphere correction).

Å FIGURE 2 Glen Innes survey of June 9, 2009, showing the distribution of reference stations with baseline lengths and the survey area with (numbered) flight runs.

Å FIGURE 3 Bathurst test of June 16, 2009, showing the distribu-tion of reference stations with baseline lengths and the survey area with (numbered) flight runs.

Glen Innes Test. FIGURE 4 shows the vertical comparison of two wide-area derived trajectories (using BALL and GFTN,

and WGGA and NWRA, respectively) against the locally de-rived trajectory (using GND1). It can be seen that once the aircraft attained its stable operating altitude, the wide-area derived trajectories are generally within 5 centimeters of the locally derived solution.

Bathurst Test. Th e Bathurst test diff ers from the Glen Innes test in that both the duration of the fl ight and the length of each run are signifi cantly shorter. FIGURE 5 shows the vertical component of fi ve wide-area derived trajectories, using several combinations of CORSnet-NSW reference stations, compared against the locally derived trajectory (using AIR2). Th e results

ÅTABLE 1 GNSS reference station combinations used in each test area.

Glen Innes Bathurst CalibrationGND1 (the local solution) AIR2 (the local solution)

BALL/GFTN BALLWGGA/NWRA BALL/GFTN

DBBO/WGGA/NEWC

WGGAWGGA/GLBN/NEWC

ÅFIGURE 5 Trajectory elevation differences for entire Bathurst calibration flight

ÅFIGURE 4 Trajectory elevation differences for entire Glen Innes flight.


Mapping | SURVEY

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once again show a remarkably consistent comparison with the locally derived solution. Data spikes showing up in the DBBO/WGGA/NEWC (yellow) solution were attributed to small data glitches at the DBBO CORSnet-NSW site. Unfortunate-ly, LiDAR data were not collected at those instances; therefore, the eff ect on ground data could not be fully assessed.

Relative ComparisonRegardless of the trajectory and orientation used to georefer-ence LiDAR data, the same number of points will be created. It is therefore possible to create a LiDAR dataset using the same raw LiDAR data but different GNSS trajectories, and compare the results to determine the relative positioning dif-ferences on the ground.

Given the large number (many millions) of points in a Li-DAR dataset, we used a representative sample of evenly spaced 10 � 10 meter areas each containing 50–100 points (on level ground) for statistical analysis. We calculated displacement vectors between points computed from the locally derived trajectory and those using wide-area trajectories. Results from fl ight run 002 at Glen Innes (see Figure 2) and run 7 at the Bathurst Calibration test site (see Figure 3) are presented here.

Glen Innes Test Run 002. Th e displacement vectors from 46 sample areas (4,620 points) are summarized in TABLE 2, being points computed using the two wide-area solutions com-pared with the locally derived solution using reference station GND1. Note the high accuracy achieved in the all important vertical component.

Bathurst Test Run 7. Th e displacement vectors from 25 sample areas (1,700 points) are summarized in TABLE 3, being points computed using the fi ve wide-area solutions compared with the locally derived solution using reference station AIR2. Once again the results clearly show that the height values agree to within a few centimeters, even over baselines of more than 600 kilometers in length.

DEM ComparisonTo investigate how the LiDAR surfaces derived from each tra-jectory compare across the entire data swath, we created raster surfaces from the LiDAR point data. Each surface was then subtracted from the local solution to create a difference sur-face. Visual inspection and interpretation was then used to discern any patterns or effects.

Th e result shown in FIGURE 6 (Bathurst Calibration fl ight

run 7) was typical of the cyclical eff ect evident for all solu-tions. Th e magnitude of the diff erence was in the order of 2–3 centimeters and is in the direction of fl ight (north to south). If this cyclical variation is compared with the trajectory com-parison for just the 33-second duration of fl ight run 7, a clear (expected) correlation with the variation in height is evident (FIGURE 7).

No DEM comparison results are presented for the Glen Innes data because of signifi cant variation in terrain and veg-etation, making interpolation diffi cult and unreliable.

Absolute LiDAR ComparisonGround control points serve two purposes in a LiDAR survey: � The calculation of statistics to describe vertical accuracy,

that is, quantifying the match of the surface to the local height datum.

� The calculation of a surface adjustment to enable trans-formation of the LiDAR points to fit the local height datum.Additionally, ground control points with accurate heights

are used to calibrate the sensor before use in active LiDAR surveys to account for internal electrical delays in the ranging and measurement system. LPMA maintains a calibration site at Bathurst Airport for this purpose, and regularly surveys the area to ensure the sensor is operating at maximum accuracy. It should be noted that the sensor was calibrated using Bathurst Airport ground control data prior to this study.

Surveyed Ground Control. Th e airport runway centerline vertical profi le for the Bathurst Calibration site (FIGURE 8) was re-computed in terms of the same IGS05 reference frame de-termined for the LiDAR trajectories, thereby allowing an inde-pendent comparison with ground truth.

Point Comparison. Data from Bathurst run 7 were used to compare LiDAR results with the established ground con-trol using a basic triangulated irregular network (TIN) surface

ÅTABLE 2 Displacement vectors for each combination relative to the local solution for Glen Innes run 002 (values in meters).

GNSS Reference Station Min. Max. Average Std. Dev.BALL/GFTN(average 200 km baseline)

East -0.008 0.029 0.011 0.008

North -0.027 0.018 -0.004 0.011

Vertical 0.004 0.045 0.025 0.009WGGA/NWRA(average 600 km baseline)

East -0.050 0.024 -0.017 0.021

North -0.106 0.083 -0.018 0.057

Vertical -0.050 0.001 -0.024 0.014

ÅTABLE 3 Displacement vectors for each combination relative to the local solution for Bathurst Calibration run 7 (values in meters).

GNSS Reference Station Min. Max. Average Std. Dev.BALL(626 km baseline)

East -0.013 -0.005 -0.009 0.002

North -0.034 0.012 -0.012 0.013

Vertical -0.031 -0.003 -0.020 0.008BALL/GFTN(average 570 km baseline)

East -0.009 0.002 -0.004 0.002

North -0.036 0.007 -0.015 0.011

Vertical -0.048 -0.014 -0.037 0.008DBBO/WGGA/NEWC(average 220 km baseline)

East -0.035 -0.026 -0.031 0.002North -0.031 -0.002 -0.016 0.008

Vertical -0.020 0.017 -0.008 0.009WGGA(280 km baseline)

East -0.024 -0.009 -0.018 0.004North -0.028 0.000 -0.014 0.006

Vertical -0.027 0.015 -0.016 0.010WGGA/GLBN/NEWC(average 210 km baseline)

East -0.006 0.004 -0.002 0.002North -0.029 0.003 -0.015 0.009

Vertical -0.020 0.017 -0.009 0.009

SURVEY | Mapping


comparison (FIGURE 9 and TABLE 4). In Figure 9, the TIN surface is indicated by the white line, while the ground control points are shown with yellow buff ers.

Th e fi rst trajectory in Table 4 is the original calibration comparison using commercial software and orthometric height data. All wide-area solutions dis-play a similar vertical off set, because of the use of diff erent reference frames for the GrafNav and wide-area solutions (IGS05 vs. GDA94), and diff erences in the implementation in software of, for

example, antenna corrections and at-mospheric modeling. At fi rst glance, the signifi cant diff erences to the GrafNav trajectory caused the wide-area result to not satisfy the accuracy specifi cations for LiDAR. However, had the wide-area so-lutions been used for the sensor calibra-tion, the fi gures would have been much closer to the ground truth.

Block-Shifted Data Comparison. In an operational environment, because of systematic errors in the resulting DEM relative to the local height datum, this

ÅFIGURE 6 Subtraction surface for Bathurst Calibration run 7 (AIR2 vs. BALL). ÅFIGURE 7 Trajectory comparison for Bathurst Calibration run 7 (031318).

ÅFIGURE 8 Runway vertical profile at the Bathurst Airport calibration site.


Mapping | SURVEY

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SURVEY | Mapping


mean vertical off set is a common occurrence with comparisons against ground control similar to those shown in FIGURE 10. Again, the TIN surface is indicated by the white line, and the ground control points are shown with yellow buff ers.

In standard LiDAR operations, the mean vertical off set between the initial results and the ground control, at the control points, pro-duces a zero-mean off set. Following this procedure in this case re-sults in the variation in the comparison of LiDAR data with ground truth now being well within the required limits of �15 centimeters (TABLE 5). Th e values show that after a block shift, trajectory so-lutions are virtually identical with a root mean square error of 32 millimeters. Th us, local GNSS reference stations can be replaced by distant CORS sites without loss of accuracy.

ConclusionsA precise wide-area positioning technique for airborne trajecto-ry solutions provides both relative and absolute accuracies simi-lar to those derived from using a local GNSS reference station. Irrespective of which reference sites are used and once calibra-tion and antenna modeling issues are addressed, the absolute comparison with ground control is well within the required accuracies. With the confi guration of a GNSS network such as CORSnet-NSW (when complete, at least one site will al-ways be within 150 kilometers of any point within New South Wales), an airborne LiDAR survey in the network’s service area can provide data for computation of an accurate sensor trajec-tory. Th is potentially negates the need to place and maintain ground reference stations close to the survey area — an exercise which not only requires signifi cant resources but also reduces the operational fl exibility of the aircraft.

Th e challenge for this technique in an operational environ-ment is to defi ne and maintain a precise reference frame for all CORSnet-NSW sites and observations, including the use of a stable ellipsoidal height datum with compatible geoid model-ing in order to provide local orthometric elevation data. Th e knowledge base required for computation of wide-area GNSS solutions is signifi cant and requires understanding of geodesy, GNSS positioning, absolute antenna modeling, application of precise ephemerides, and derivation of the other parameters in-herent to successful ambiguity resolution over long distances.

Regardless of processing method, a LiDAR survey will always require independent ground surveys for collection of vertical checkpoints, which provide quality control to ensure the accu-racy meets specifi cations, and the means to defi ne any transfor-mations necessary to fi t LiDAR data with local height datum.

ManufacturerNovAtel’s WayPoint GrafNav software (www.novatel.com) was used for comparison purposes. �

OSCAR L. COLOMBO received a degree in electrical engineering from the National University of la Plata, Argentina, and a Ph.D. in electrical engineering from the University of New South Wales, Australia. He is an independent consultant.

SHANE BRUNKER is an airborne LiDAR and imaging specialist working in a consulting capacity for specialized LiDAR survey company Network Mapping (United Kingdom).GLENN JONES is a senior surveyor at the NSW Land and Property Management Authority in Bathurst, Australia. VOLKER JANSSEN is a GNSS surveyor (CORS Network) in the Survey Infrastructure and Geodesy branch at the NSW Land and Property Management Authority in Bathurst, Australia.CHRIS RIZOS is head of the School of Surveying and Spatial Information Systems of the University of New South Wales, has a surveyor’s degree and a Ph.D. from the same university, and is an specialist in geodesy and GNSS positioning.

ÅFIGURE 9 Comparison of LiDAR surface and ground control points.

ÅFIGURE 10 Usual operational comparison of LiDAR surface and ground control points.

ÅTABLE 4 Comparison of LiDAR surface against ground control points (all values in meters).

Trajectory Mean Min. Max. RMSEAIR2 (commercial software) 0.008 -0.074 0.097 0.034

AIR2 -0.102 -0.177 -0.002 0.106BALL -0.102 -0.177 -0.002 0.106BALL/GFTN -0.117 -0.191 -0.015 0.122

DBBO/WGGA/NEWC -0.089 -0.161 0.009 0.094WGGA -0.098 -0.170 0.000 0.103WGGA/GLBN/NEWC -0.090 -0.164 0.008 0.096

ÅTABLE 5 Comparison of block-shifted LiDAR surface against ground control points (all values in meters).

Trajectory Mean Min. Max. RMSEAIR2 (commercial software) 0.000 -0.082 0.089 0.033

AIR2 0.000 -0.075 0.100 0.032BALL 0.000 -0.075 0.100 0.032BALL/GFTN 0.000 -0.074 0.102 0.032

DBBO/WGGA/NEWC 0.000 -0.072 0.098 0.032WGGA 0.000 -0.072 0.098 0.032WGGA/GLBN/NEWC 0.000 -0.074 0.098 0.032

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