Multi-Agent Airborne Laboratory for Cryospheric Remote Sensing

Final Report

Shawn Keshmiri, Mark Ewing, Richard Hale, Carlton Leuschen,

John Paden, Fernando Rodriguez-Morales and Jie Yan

University of Kansas

2335 Irving Hill Road

Lawrence, KS 66045-7612

http://cresis.ku.edu

Technical Report

CReSIS TR 164

May 30, 2016

This work was supported by grants from

the Paul G. Allen Foundation and the National Science Foundation

(#ANT-0424589)

FINAL REPORT

Directions: Respond to the questions below for the report narrative, and make

sure to address activities and outcomes for the entire grant period. Also attach a

final project budget report and key materials associated with the grant project in

the attachment section of this report. Thank you.

Request ID#

11708

Organization Name

Kansas University Endowment Association

Grant Amount

199358

1) Please provide a brief summary of the overall completed project.

Please limit word count to no more than 300 words.

The lack of fine resolution bed topography near the grounding lines of fast-flowing

temperate glaciers, and an incomplete knowledge of basal conditions, have been major

impediments to testing and validating ice-sheet models and reducing uncertainties in

projecting rates of sea level change [1-9]. The surface of fast-flowing glaciers is heavily

crevassed and extremely rough, and often contains debris and water. Scattered signals

from the rough ice surface and ice volume mask weak bed echoes from the ice-bed. Thus,

airborne radar sounding of temperate glaciers and fast flowing glaciers near their terminus

is a major challenge in radio glaciology [10-11].

In 2013, researchers at the University of Kansas’ Center for Remote Sensing of Ice Sheets

(CReSIS) proposed to PGAFF the development of new dual frequency HF/VHF radar and

unmanned aerial system (UAS) technologies capable of sounding fast-flowing temperate

glaciers in polar regions. This proposed development was based on prior work conducted at

the University of Kansas on both low frequency coherent sounders and UASs [Gogineni, S.,

Private communication & 12-17] as well as other studies reported in the literature [18-21]

Our team made excellent progress in developing state-of-art radars and key UAS

technologies to collect previously unattainable fine-resolution data from fast-flowing

temperate glaciers. By leveraging logistical and other support from National Science

Foundation, these UASs and radar technologies were evaluated in a polar mission in

Western Greenland. Eight over-the-horizon UAS flight tests were performed, covering more

than 400 Km. Quality science data were collected over areas previously surveyed using

VHF and HF sounders, which were operated onboard manned aircraft as a part of NASA

Operation IceBridge and JPL’s Warm Ice Sounding Explorer (WISE) mission, respectively.

The results presented in this report show that the new UAS-based HF sounder images are a

substantial improvement over previous VHF and HF sounder images.

2) What measurable outcomes* described in your original proposal were achieved?

A. Measureable Outcomes

This project involved interdisciplinary research in sensors, remote sensing, bio-inspired

control of multi-agent UASs, and education of the future workforce. The research plan aimed

at developing technology on the following thrusts: (1) low power and light weight airborne

dual-frequency HF/VHF radars integrated into two UASs with optimized antenna

configurations; (2) Integration of biologically-inspired discrete swarm guidance and control

laws to ensure the long term stability and coherency of the swarm, inter-collision avoidance,

and obstacle avoidance in an unstructured and uncertain environment; (3) optimized,

decentralized, nonlinear model predictive controllers (NMPCs) for UASs with a built-in

frequency-dependent robustness to maintain team coordination in real-time, satisfy

proximity requirements of airborne sensors, meet ground tracking precision requirements,

and control airborne sensors in unsteady, dynamically changing, noisy, and uncertain

conditions; and (4) Demonstrate performance of the new technology in survey flights using

UASs.

B. Dual Frequency Radar System

Two compact radar modules (designated HFS3 and HFS4) with enhanced GPS capabilities

were fabricated. The radars were improved replicas of the system reported in [17]. The radar

GPS system was upgraded to improve both in-flight and post flight position solutions. A small

circuit based on the OEM625

GPS chip from NovAatel Inc and

a data logger were

implemented. The circuit was

integrated into the radar chassis

without penalty in weight or

volume. The GPS upgrade

enabled centimeter-position

accuracy for better

georegistration of the radar

data. GPS timing

synchronization across multiple

radars will also enable bistatic

measurements in the near

future. Figure 1 shows a

photograph of the radar system

installed in the G1X platform.

The top inset shows a

photograph of the upgraded GPS

circuit. The bottom inset shows

the computed accuracy of the processed GPS solution indicating a standard deviation of less

than 6 cm for the height and less than 3 cm for position in the eastward and northward directions.

Figure 1: Photograph of HFS3 installed inside the G1XB UAS fuselage. The radar

is highlighted in yellow. The inset shows a photograph of the upgraded GPS

subsystem (top) and a plot of the estimated accuracy of the GPS solution (bottom).

The current radar modules employ power amplifiers and transmit/receive (T/R) switches with

a peak power capability of 100-W. This effort was partially supported by this grant with

additional funds from the

CReSIS NSF grant. To

further improve the

radar sensitivity, we

developed a custom T/R

module capable of

producing up to 1000-W

of peak power. A

prototype circuit

compatible with the

existing radar housing

was designed, built, and

successfully tested as a

proof of concept. A

photograph of the circuit

is shown in Figure 2

along with some measured performance metrics. The module will be available for future

missions and will help improve the sensitivity of the radar by almost an order of magnitude.

C. Radar Antenna Integration and Performance

Two new radar antennas resonating at 14 and 35 MHz were designed, built, and integrated

for the G1X UASs. Before UAS over-the-horizon radiation science missions, 16 short in-flight

antenna measurements were performed to verify the radar system’s bandwidth. Some of

these flights were dual-purpose and allowed us to test key UAS subsystems in parallel. Figure

3 shows a comparison between in-flight measured and simulated antenna return loss in both

frequency bands.

While we achieved approximately 10% bandwidth at both frequency bands using custom

designed matching networks, there was a slight degradation in antenna bandwidth observed

(~0.5 MHz). The degradation is attributed to the interactions with the avionics cablings or

in-flight dynamics. We are currently working on a high-fidelity model of the radar antennas

in the presence of the airframe, avionics, and cablings to improve the antenna bandwidth.

In the future, we also would like to explore the concept of the antenna matching technique

proposed by Rhea [19] which was demonstrated to match a monopole antenna to 50 Ohms

from 7 to 14.3 MHz. This will allow us to significantly improve the operating bandwidth of

Figure 2:(a) Photograph of the 1kW (60 dBm) T/R module developed for future operation

with the HF sounder; measured peak output power as a function of input power and biasing

conditions for (b) 35 MHz and (c) 14 MHz; (d) measured switching speed of the T/R with

turn-on time of 1.5 s and turn off time of 1.35 s.

Figure 3: A comparison between in-flight measured and simulated antenna return loss in both frequency bands.

the radar, thereby increasing the vertical resolution to better resolve fine details in the ice

bed topography.

D. UAS Technology

To achieve scientific and engineering objectives of the PGAFF project, five UASs ranging from

9 to 76 lbs. were designed, manufactured, instrumented, and flight tested. The flagship UASs

for the radar instrumented missions were called G1XB and G1XC. The G1XB/C UASs are 10

lbs lighter and have 30 minutes more endurance (1 hour 15 minutes) than the original G1X

UAS that was flown in earlier ice-sounding missions in 2013-14 in Antarctica.

The new radar antenna design allowed the KU team to fly shorter wings than were flown in

the Antarctica mission (2013-14). Based on the radar's reduced wingspan requirement and

the attendant reduction in wing bending moment, the decision was made to fabricate the

wings with balsa, spruce, and bass wood. The upshot of this design change was that the

aircraft weight was reduced by approximately 5 lb. The strength of the new wing was

validated through both analysis and tests. The wing survived the 6 g load and was loaded to

approximately 8 gs before it failed. To reduce the G1X takeoff weight further, a smaller but

more powerful engine (Desert Aircraft DA-120) was tested extensively in the KU Aerospace

Propulsion Lab. DA-120 engine thrust, torque, fuel consumption ratio, and rotations per

minute (rpm) were recorded as a function of throttle position and a new dynamic model was

developed. Considering the fact that engine thrust and fuel consumption ratio are function

of propeller size and design, six different composite and wooden propellers with different

diameters and pitch angles were tested on the DA-120 engine. Thirty-six tests were run to

find the most optimal propeller to improve overall system performance. The chosen propeller,

Falcon 28x10, reduces the overall fuel consumption by 5%, which is very significant in the

aerospace contexts. With this propeller, the engine maintains the required thrust at a lower

rpm which results in lower fuel consumption and increased UAS range. Propulsion static tests

were verified during the 2016 Greenland mission. An all new and lighter avionics box was

designed and integrated into the G1X UASs. Systems wiring was updated and new, lighter

MIL-STD connectors were used to reduce the takeoff weight of the UAS and increased

robustness of UASs. Modifications to the avionics box, wings, wiring, and propulsion system

resulted in a 12% reduction in the new G1X UAS weight compared to the original G1X. The

overall weight was reduced from 86 lbs. to 75 lbs. This weight reduction is expected to

increase the G1X UAS range by 33% from 90 km to 120 km if it carries the same payload.

The manufacturing and system integration of two new G1X UASs were completed in 2015.

E. Dynamics and Control of Multi-Agent UASs

In recent years, swarming robots and aircraft have been studied extensively. However,

swarming aircraft are assumed to be 2-D point masses with no aerodynamic effects.

Controlling multi-agent airborne aircraft in tight formation with high velocity and inertia in

an unstructured environment is exponentially more complex than existing studies show. To

address these challenges, and to enhance performance of autonomous and collaborative

UASs, we conducted a fundamental study on the guidance, navigation, and control of self-

organizing fixed-wing UASs in three-dimensional space, using the moving mesh partial-

differential equation approach. The objectives were: (1) Develop trajectory generation logic

for a swarm of UASs which uses topological distances instead of metric values. Biologically

inspired, this method evades exploiting distance measurements in the absence of such

capabilities, as it happens in swarming birds [23-25];(2) Develop built-in collision avoidance

mechanisms to keep the formation as uniform as possible and prevent UASs from crossing

over or tangling [23-33]; (3)Validate flexibility and coherency of agents in following an

arbitrary sinewave-like, or curvature shaped flight formation; (4) Identify the aerodynamics

of UASs in the presence of environmental disturbances (e.g. cross wind or windsheer) and

validate the robustness of agent controllers [23-30]. A dozen papers were published on

guidance, navigation, and control of multi-agent UASs and unsteady and nonlinear

aerodynamics of UASs in prestigious national and international journals and conferences [20-

37].

For the first time in the history of UAS control, the KU team was able to develop a new

autopilot system that is capable of running computationally intense control (e.g. Nonlinear

Model Predictive Control) and artificial neural network-based system identification algorithms

in real time [37]. The new autopilot allowed the KU team to successfully validate the

developed guidance and control swarm algorithms between actual and virtual UASs in real-

time [Ref: Year 1 Progress Report].

F. UAS Flight Tests

The complexity of flight test on polar missions is an order of magnitude higher than flight

tests in the continental U.S. Successful UAS missions in polar regions are highly dependent

on the UAS reliability and demands for extensive crew training. The University of Kansas has

obtained nine certifications of authorization (COAs) from the Federal Aviation Administration

(FAA) to test UASs locally in Lawrence, Kansas. Local flight tests made frequent UAS

reliability tests and crew training more achievable and affordable. More than 200 UAS

validation and verification flight tests were successfully conducted in Lawrence Kansas prior

to Greenland deployment. Multiple UAS platforms were used in these flight tests including

the 40% scale Yak-54, Bird of Time, DG808, and G1X UASs.

With the support from the National Science Foundation, the successful UAS flight test

campaign in Lawrence, Kansas was followed by a polar mission in March- April 2016. The

Russell Glacier, a fast flowing glacier located northeast of Kangerlussuaq, Greenland, was

targeted for this science mission. Three different UAS platforms were flight tested 32

autonomous flights. To complete the science mission, the G1XB UAS was instrumented with

35 MHz radar. The UAS flight tests were conducted from two frozen lakes in proximity to the

Russell Glacier. Although the extreme weather (very cold and very windy), specific

geographic location of lakes (surrounded by high mountains), and manned aircraft flight

operations in the area increased the complexity of this polar mission by an order of

magnitude, the CReSIS UAS was able to successfully perform eight (8) over the horizon

missions covering about 400 km of ice sheets. The G1XB UAS was able to follow the glacier’s

steep slope and collect data over closely spaced lines (3.65~24 m) (see Figure 4). It is

extremely difficult for manned aircraft to hold altitude/heading @ 400-600 ft above the

ground level with relatively slow speed (30 m/sec) and to collect data over such closely

spaced grid lines, yet we were able to achieve this success using UAS for the first time during

this mission [38].

Figure 4:3D Trajectory of G1XB UAS over the Russell Glacier, Kangerlussuaq, Greenland. The top-right inset shows the

crevassed surface along the flight path, which makes radar sounding a challenge.

G. Results

We collected science data over three previously flown flight lines. During these previous

missions, we collected VHF (180-210 MHz) radar sounder data on these lines. The three

lines were chosen to represent a range of image quality from poor to good. In all cases, the

new HF sounder images are a substantial improvement over the VHF sounder images. The

HF sounder is also compared with data collected by the JPL WISE HF sounder (Rignot 2013

[39-40]). We also began work on 3D imaging and show some preliminary work. Additional

time is needed to tune the processing parameters, estimate and remove noise sources,

validate system parameters and performance, and finally to test different types of 3D imaging routines.

Figure 5 shows a map of the 3 images used for comparison. The good quality line is green;

the medium quality line is yellow; and the poor quality line is red. Figure 6 compares each

of the lines between new HF sounder data and VHF sounder data. Where the VHF sounder

is able to see the ice bottom, the HF sounder matches it. In many places the VHF sounder

cannot see through the temperate ice layer which sometimes starts only a few tens of

meters below the ice surface – completely obscuring and attenuating the ice bottom in

many regions. The HF sounder is able to sounder nearly 100% of the ice bottom including

many regions where no ice bottom is detectable in the VHF imagery. The HF sounder, with

its long wavelength, is much less sensitive to the temperate ice water inclusions and

crevassing. Note that the nearly horizontal line at ~300 m depth in each VHF image is the

ice surface multiple: this is a multiple reflection or resonance between the large P-3 aircraft

and the ice surface. Figure 7 shows the WISE data from a line which crosses all three

CReSIS HF sounder lines. The intersections with the good, medium, and bad lines are

shown by the vertical bars. The corresponding intersections are also shown in Figure 6 with

a blue line. The ice bottom is difficult to impossible to detect in the WISE data and demonstrates the improved performance of the CReSIS HF sounder over the WISE system.

The first step in 3D imaging is to co-register the different passes. We have completed this

first step for the six passes over the good quality line. Figure 8a shows the phase of the

interferogram formed from two overlapping passes. The bright ice surface and ice bottom

are phase-coherent and standout from the noisy background. Because the scattering from

the ice surface and bottom mostly comes from the nadir direction, the phase is consistent

and near zero angle (cyan colored). The ice surface is flatter than the bed and we use it to

verify that the coregistration angle is small in Figure 8b. Some variation about zero angle is

expected since the ice surface does have some roughness due to crevasses and the overlap between the two flights is not perfectly zero.

Figure 5: Map showing the HF sounder data lines used for comparison over Landsat-7 imagery. The good quality line is green, the

medium quality line is yellow, and the poor quality line is red.

Ice Bottom

TemperateIce Layer

Ice Bottom

MissingIce Bottom

Ice Bottom

Ice Bottom

Ice Bottom

Ice Bottom

SurfaceMultiple

SurfaceMultiple

Figure 6: a) through f) HF and VHF sounder comparisons for good, medium, and poor quality lines. The point of intersection with the

WISE line is shown by the blue line.

a) b)

Figure 7: a) Comparison with WISE HF sounder data. The intersection with the good (green), medium (yellow), and poor (red) quality

lines are shown. The location of the ice surface and ice bottom detected by the CReSIS HF sounder is shown with an ‘x’. b) Magnified

region around the ice bottom shows that the WISE HF sounder data quality is significantly lower than the CReSIS HF sounder.

Ice Surface

Ice Bottom

a) b)

Figure 8: Phase coherence from co-registration of multiple passes. a) Phase-angle map of the interferogram formed from two overlapping

passes taken on two different flights. The ice surface and ice bottom show good coherence whereas the background noise has poor

coherence and the angle varies rapidly from pixel to pixel. b) The angle extracted from the strong ice surface in a).

3) What outcomes were not achieved?

As discussed in section 2.D, well-grounded research and experiments were conducted on

the swarm of multi-agent UASs. Additionally, all required hardware and software for such

missions were designed, developed and verified. However, flight test of multi-agent swarm

of UASs is pending due to Federal Aviation Administration (FAA) UAS regulations. The FAA

regulations prohibit any multi-agent flight test in U.S. airspace. KU has been in negotiation

with the FAA since 2014 and we anticipated receiving special authorization for operation of

multi-agent UASs in near future.

4) What barriers, if any, prevented you from achieving all of the expected outcomes? How

did you overcome the barriers during the grant period?

Lack of transparent UAS flight test regulations from 2014-15 was a major hurdle for our

flight test activities. Although KU filed for the UAS certification of operation in 2014, we had

to wait till May 2015 to receive approval from the FAA for UAS flight test in South West of

Lawrence Kansas. During this period, we closely collaborated with the U.S. Army to flight

test our UASs in their restricted area in Fort Riley, Kansas. More than 60 UAS flight tests

were conducted at Fort Riley, Kansas which is home of the 1st Infantry Division. KU UAS flight

test operation in Fort Riley was continued till February 2015 when the FAA forced the U.S. Army to shut down our UAS operation. UAS flight test operation was put till June 2015.

The European UAS flight test regulations were no less complex compared to the U.S. FAA

regulations. It took KU 18 months to negotiate UAS flight test operations in the Greenland

airspace. The complexity of this process was compounded by the need to convince both the

Danish Transpiration Authority and Greenland Air Traffic Control that our UAS operation is

safe. Our approval process was further exacerbated because of the proximity of Russell

Glacier to the Kangerlussuaq International Airport which is the main hub of manned aircraft

operations in Greenland with many daily flights. Fortunately, KU’s prior history in UAS flight

operations in the U.S. and in polar regions helped us to receive permission to flight test all

our UASs in western Greenland; however, the flight test multi-agent UASs was not

approved until similar flights are conducted in U.S.A. and proven to be safe. In the absence

of swarming UASs, the concept was proven using one UAS flight multi-pass on a closely

spaced grid (see Figure 4).

5) What strengths and unexpected opportunities helped you achieve your outcomes?

In addition to the kind support from the PGAFF, it is extremely important to mention the

importance of matching funds from the National Science Foundation and the University of

Kansas. These resources were vital to achieving this initial validation of the proposed concept

in polar regions. We would not achieve any of scientific outcomes shown in Section 2. F, if it

was not for logistical support of National Science Foundation. By partnering with the PGAFF,

we were able to incorporate important improvements to the design and fabricate state-of-

the art radars and UASs for our studies. By leveraging federal and local support from the NSF, Fort Riley, KU, and the PGAFF we had the resources to deploy our team to Greenland.

Very recently, KU was granted a blanket certification of operation (COA) by the FAA for

UAS flight test operation in May 2016. This permission allows KU to perform UAS flight

tests anywhere in the continental U.S. as long as the UAS weighs less than 55 lbs and

flight test is conducted under 400 ft. AGL in a class-G airspace.

6) What other benefits, if any, has the grant project provided your organization or the

larger community?

The support of PGAFF has made a significant contribution to operational research on the

cryosphere with a domino effect on a multitude of Earth and Science disciplines. While our

proposed concept was transformative, it had yet to be proven viable. Thus, this seminal

investment from the PGAFF award made the creation of this high-risk, high-reward project

possible, and it was necessary to bridge the gaps in what can be supported at an early stage

by federal dollars. Without the support of PGAFF, we would not have had the resources to

launch a successful demonstration of this unproven, yet innovative technology and its

application as a pilot program. When innovative technology ideas are still too early stage for

federal support, it is critical to have the partnership of foundations to bridge this gap and

enable the proof of concept demonstration. Furthermore, as federal investments remain

scarce, the ability to leverage partnerships like ours with PGAFF can help us to unlock federal

support down the line by demonstrating the value and potential of our research to better

understand climate change in these difficult to characterize, yet very instrumental, regions

of glaciers and ice sheets.

Emerging ice sheet models for glacial flow require fine resolution data near the terminus of

key glaciers. With the support of the PGAFF, we demonstrated that achieving the resolution

required to reduce uncertainties in projecting rates of sea level change can only be

accomplished with a UAS flight based radar system.

7) For questions A & B below: If your project outcomes included serving

individuals, please indicate the number of people and characteristic of those

served in the questions below.

A.1. Indicate the number of individuals served below.

N/A

A.2. Indicate the primary characteristic of the individuals served (e.g., general program

participants, audience, youth).

Please select N/A if not applicable to your project.

N/A

B.1. If your grant outcomes include serving a second cohort of people, list below how many

were served.

N/A

B.2. Indicate the primary characteristic of the individuals served (e.g., general program

participants, artists, youth).

Please select N/A if not applicable to your project.

N/A

Attachments

Final Budget Report [Required]: Attach a final project budget below (reflecting a budget-to-

actual financial report). Include a budget narrative that explains how grant funds were

spent and notes important deviations from the original grant budget.

Please see attached financial report and justification.

Products Associated With the Grant Project: To help us better understand work completed

during the grant period, please submit the following attachments. (If you have multiple

documents for each of the categories below, upload each document along with the

respective Title in the dropdown list below).

A. Any key press or promotional materials associated with the grant project.

A bibliography of related publications is attached.

B. Significant work products (including evaluation reports, strategic plans, fundraising or

communication plans). Also include programs or major materials developed through the

grant project. Note: If any work product, such as videos or programs, cannot be attached

you may send it in by mail to our office.

Flight Test videos were shared with our project manager, Spencer Reeder, and

thousands of photos were taken during domestic and Greenland flight test

activities that can be shared with the PGAFF upon request.

C. The Foundation regularly updates its Web site with photos and descriptions of grant

projects. If you have photos from the project that you would like us to consider posting to

the Web site, please submit them (up to six photos total). By submitting photographs you

grant the Foundation a non-exclusive, transferable, royalty-free license to use and display

these photographs for non-commercial purposes. If a photo credit is required, please

include appropriate credit information.

We have previously submitted a blogpost for the PGAFF website, and we are

delighted to provide an updated blogpost upon request.

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