M.L. Stone and J.R. Anderson

Advances in Primary-RadarTechnology /'.'

Current primary radars have difficulty detecting aircraft when ground clutter, rain, orbirds interfere. To overcome such interference, the Moving Target Detector (MTD) usesadaptive digital signal and data processing techniques. MTD has provided the founda­tion for a new generation ofprimary radars called Airport Surveillance Radar-9 (ASR-9).In addition to achieving near-optimal target-detection performance, ASR-9 also prOVidestimely weather information. The Federal AviationAdministration (FAA) is installingASR­9 systems at more than 100 airports across the United States.

,-

While the role ofbeacon (or secondary) radarsin air traffic control is growing, there is a con­tinuing need for primary radar in providingaircraft position data. In addition to aircraftsurveillance, primary radars provide air trafficcontrollerswith timelyweather information thatcan be used to direct airplanes flying in or nearhazardous weather.

Originally, primary radars were magnetronsystems eqUipped with a single fan-beam an­tenna mounted on an azimuth rotator. Laterversions incorporated Moving Target Indicator(MTI) detectors, whichused delaylines to cancelground clutter. MTI radars, however, have diffi­culty detecting aircraft when ground vehicles,rain, or birds interfere.

To handle such adveJ;:se"conditions, the Air­port Surveillance Radai-9 (ASR-9) [1], a next­generation primary radar, uses the MovingTarget Detector (MTD) [2-4] concept. MTD em­ploys several adaptive digital signal and dataprocessing techniques. For example, Dopplerprocessing eliminates ground and rain clutter.Doppler processing is followed by a number oftarget editing steps; e.g., a ground-clutter maprejects false alarms that result from mountainsand buildings. In another instance, fixed andarea (adaptive) thresholds eliminate echoescaused by flocks of birds or clutter due tovehicular traffic such as automobiles andtrucks. MTD achieves further reduction offalsealarms with a surveillance-processing modulethat uses scan-to-scan correlation for rejecting

The Lincoln Laboratory Journal, Volume 2, Number 3 {1989j

targets that fail to meet spatial or temporal cri­teria. As a result of MTD processing steps onequipped radar, ASR-9 can deliver, via tele­phone lines, a set of target reports free of theclutter and false alarms found in earlier airportprimary radars.

ASR-9 also has a separate weather channelthat provides concise and timely reports onstorm intensities and positions. An air trafficcontroller can select and display any two of sixNational Weather Service (NWS) intensity levelsto obtain an accurate representation of thelocation of any storms that might be hazardousto aircraft.

The MTD processor architecture was devel­oped dming the 1970s under Federal AviationAdministration (FAA) sponsorship by a LincolnLaboratory team [2-6]. The team, led by C.E.Muehe, chose a technique that used block­staggered groups ofpulses to detect any targetsmasked by intense rain clutter. Initially, theteam constructed and field-tested a hard-wired(nonprogrammable) system. A parallel micro­programmed processor (PMP) version called theMTD-II followed in the late 1970s. PMP [7, 8]facilitated MTD's ability to adapt to differentenvironments, a feature deemed necessary tooptimize the system's performance at a variety ofsites. Subsequent tests ofthe MTD-II processorsin challenging environments demonstratedtwo benefits: reliable, essentially clutter-freedetection; and a reduction in the false-alarmrate superior to that attained by earlier radar:s

363

Stone et aI. - Advances in Primary-Radar Technology

(a)

(b)

Fig. 1-Detection of aircraft flying in rain. (a) Output of aconventional MTI radar taken with a 5-min exposure. Theaircraft flying within the rain echoes is obscured. (b) Outputof moving target detector (MTD). The screen is free of rainclutter and the overall track of the aircraft is clearly deline­ated. Because only one display was available, the photo­graphs were made sequentially.

364

[9, 10). Figure 1gives a qualitative illustration ofthe superiority of MTD over MTI in detectingaircraft flying in rain.

MTD and the weather channel used in ASR­9 represent a significant improvement in pri­mary-radar technology. The FAA is installingASR-9 systems at more than 100 major airportsin the United States (Fig. 2). This article firstdelineates the primary-radar requirements foraircraft and weather surveillance. Next, MTD isdescribed and the system's test results are dis­cussed. Finally, we comment on possible futureenhancements to the MTD concept.

Performance Requirements forAirport Primary Radars

Table 1 gives the performance requirementsof an airport primary radar. The requirements,which are embodied in our current MTD model,place extreme demands on primary-radar per­formance. It is essential that a primary radar• reject ground clutter by at least 40 dB,• continue to perform in the presence ofrain,• adapt to limit the false-target reports gen­

erated by birds and vehicular traffic suchas automobiles and trucks, and

• eliminate any additional clutter break­through by means of scan-to-scan pro­cessing.

Moving Target Detector

The main improvements of MTD over itspredecessor, MTI, are that MTD performs cluttermitigation by means of digital Doppler filterprocessing and the use of false-alarm-ratethresholds. Other adaptive features of MTDeliminate bird echoes and vehicular traffic. Theoverall processing reduces the output to tele­phone-line bandwidth.

Figure 3 shows a block diagram of the MTDsystem, which includes a dual fan-beam eleva­tion antenna (Fig. 4). Transmission takes placethrough the lower beam. The upper beam re­ceives echoes at close range, which reduces thestrength of the echoes that result from groundclutter. The lower beam is used for distanttargets; its minus 3-dB point is typically di-

The Lincoln Laboratory Journal. Volume 2. Number 3 (J 989)

'.

: ; .,

Stone et aI. - Advances in Primary-Radar Technology

. .: :

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Fig. 2-Planned ASR-9 installations in the United States.

rected toward the horizon.Although the antenna normally both radiates

and receives vertical polarization, wheneverthere is heavy precipitation over a significantportion of the coverage area, the radar switches

to circular polarization. By doing so, the sensorachieves an additional 12 to 20 dB ofprecipita­tion-echo rejection. During the time that circu­lar polarization is used, weather signals arederived from the orthogonal-polarization ports

Table 1. Surveillance Requirements for MTD-Based Airport Primary Radars

• Maximum range =60 nmi.• Altitude coverage =0 ft to 25,000 ft.• Update rate = 4.8 s.• Probability of detecting a small aircraft = 0.9.• False-alarm rate at the output of a tracking filter = 1 per scan.• False-alarm rate at the output of the correlation and interpolation filter = 20 per scan.• Range accuracy = 1/32 of a nautical mile with a 200-ft rms.• Azimuth accuracy =0.16° rms.• Capacity = 400 aircraft distributed nonuniformly in azimuth.• Weather reporting: six National Weather Service (NWS) levels are available for

pairwise selection by the air traffic controller.

The Lincoln Laboratory Journal. Volume 2. Number 3 (1989) 365

Stone et aI. - Advances in Primary-Radar Technology

Correlationand

Interpolation

I·

,

DisplayableTargetReportsw/Flags

Surv.Proc.

Scan-to-ScanCorrelation

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Fig. 3- MTD-II block diagram.

of the antenna. Meanwhile, the target signalsare received through the same ports of theantenna that are used when linear polarizationis radiated. Multiple-channel rotary joints carrythe information of the received signals to theprocessing units, which are located in a shelterat the base of the antenna tower. During opera­tion with circular polarization, a switch locatedon the antenna selects either the weather-chan­nel upper or lower beam. The signal from theselected beam is then passed through a singlerotating joint to the weather-channel receiver.

Signals for target detection pass from theantenna through a sensitivity time control anda low-noise amplifier. After the signals areheterodyned to an intermediate frequency,they are translated to baseband at the output ofa linear receiver. This step provides in­phase and quadrature video signals, which AIDconverters sample.

There are two coherent processing intervals(CPI) for each beam dwell, and each beam dwellcommences in synchronism with a bearingpulse from the shaft encoder that reports theantenna's position. In the case of ASR-9, theindividual CPIs in the CPI pair use 8 and 10pulses, respectively, with a nominal averagepulse-repetition frequency (PRF) of 1,000 Hzand a nine-to-seven ratio between the twoCPIs. Fill pulses account for variations in theangular rate of the antenna that result fromwind effects.

For each of the 8 or 10 CPI periods, the pro-

366

cessor's input memories store the signals forthe 960 range gates, which span 60 nmi. Theprocessor then performs saturation and inter­ference testing of the digital signals, followedby Doppler filtering and thresholding. Finally,range, azimuth, Doppler amplitude, and qualityvalues are delivered for the targets in the rangecells that contain detections. (A quality value[11) indicates the expected azimuth estimateerror.) A detection occurs whenever a thresholdis crossed in a particular range cell of roughly150 m. The detections are then correlated andinterpolated; i.e., the reports are correlated andcentroids are found for the range and azimuthmeasurements. After the reports are subjectedto additional criteria for false-alarm rejection,they are passed to a scan-to-scan correlatorthat reduces the output false-alarm rate toabout one per scan.

The MTD Processor

The MTD processor performs several func­tions: signal processing, thresholding, post­detection processing, area thresholding, andscan-to-scan correlation.

Signal Processing

MTD's central functional element is a set ofDoppler filters, typically 8 or 10 for each rangecell or sample. The output of the filters are allindividually subjected to thresholds [1,12). The

The Lincoln Laboratory Journal. Volume 2. Number 3 (1989)

\

input to the filters is derived from the output ofthe quadrature video detectors, which aresampled by two 12-bitAjD converters operatingat a rate of 1 MHz. For each 4.8-s revolution ofthe radar antenna, there are 256 azimuth beamdwells, each of which contains two CPls. Foreach CPI, 960 range cells are processed. Thus,after every revolution of the antenna, more than4 million Doppler filters are formed. The outputsignals of the Doppler filters are examinedby the signal processor, which uses thresholdcriteria appropriate to the desired false-alarmrate and to the locations of the signals rela­tive to several factors: ground clutter, precipi­tation echoes, and the number of bird echoesencountered.

To obtain acceptable performance in condi­tions of rain- and ground-clutter interference,the developmental model of MTD used a set ofeight finite impulse-response filters for eachrange cell. Two pulse-repetition intervals wereused to prevent the masking that occurs whenrain clutter obscures a target. (Masking can alsoresult when the target Doppler frequency is anear integer multiple of the PRF.)

As noted, the filter design in ASR-9 employs

Fig. 4- ASR-9 antenna. Networks used to change the an­tenna's polarization from linear vertical to circular havebeen installed adjacent to the two feed horns that form theupperand lower beams. (Photo courtesy of WestinghouseElectric.)

The Lincoln Laboratory Journal. Volume 2. Number 3 (1989)

Stone et aI. - Advances in Primary-Radar Technology

either 8 or 10 samples of 12-bitwords to improvethe system's detection at ranges affected byground clutter. Optimum filter characteristicswere obtained by making the time span of theCPls equal; Le., 8 pulses were used at a lowrepetition rate and 10 pulses were used at ahigh repetition rate.

Thresholding

Primitive target reports are declared from theoutput of the filters after the data are subjectedto certain thresholds. (The targets are calledprimitive because they have not yet been asso­ciated with other criteria.)

The output of the zero-velocity filter is sub­jected to a threshold value equal to the single­pole average of the clutter values that wereobserved in the subject range cell over 10 to 20scans. The values are updated every other scan.The thresholding processor uses a multiplier toattain a false-alarm rate on the order of 10-5 .

A sliding-window, constant false-alarm rate(CFAR) threshold is used to determine the rangethresholds for the nonzero-Doppler-velocityfilters. The CFAR processor calculates a thresh­old by averaging the six cells preceding andseven cells following an interval that includesthe range cell under test and the two adjacentcells immediately preceding and following thatrange cell. (Thus the total window, which is ap­proximately 1 nmi long, includes 16 range cells.)Appropriate adjustment is made to achieve a10-5 false-alarm rate. In range cells affected bysevere ground clutter, the CFAR threshold isincreased by a fraction of the zero-filter output.The goal of the CFAR processor is to achieve arate of 60 to 100 false alarms per scan.

To improve the system's ability to distinguishbetween two neighboring targets with similarDoppler velocities, ASR-9 uses a more sophisti­cated algorithm than the original version ofMTD. (Whenever targets were separated by lessthan 0.5 nmi, the MTD-II algorithm had a lowprobability ofresolving them [11.) In determiningthe interference level used for the threshold, theASR-9 CFAR algorithm eliminates the threestrongest samples within the CFAR window. Agreater ojcriterion is also employed to choose

367

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Stone et aI. -Advances in Primary-Radar Technology

between the interference power of the precedingand following groups of range cells adjacentto the cell under test. Analysis indicates thatthis algorithm, which Westinghouse ElectricCorp. developed, can resolve targets as close as0.25 nmi.

Post-Detection Processing

Using post-detection processing. we can re­duce the aforementioned false-alarm rate toone false alarm per scan when averaged over aIO-scan interval. In post-detection process­ing. thresholded target reports are subjectedto additional filtering. The filtering removesground clutter that exceeds the design charac­teristics ofthe filter bank. Ahigh-spatial-resolu­tion map (0.25 nmi x 2.8°) is employed to selectthe appropriate threshold values: for the groundclutter, a Doppler weighting that corresponds tothe scanning modulation; and. for the groundtraffic. a flat-topped Doppler weighting. Nterthis operation is completed. the reports arecorrelated and interpolated.

In MTD. targets are grouped in accordancewith their spatial adjacency (Fig. 5). The cen­troids of the different groups are then calculatedfrom a center-of-mass estimation (first momentweighted by amplitude). Each centroided targetreport is given a quality value: an integer rangingfrom 0 to 3 that indicates the number of detec­tions that were made as the antenna scannedpast the target. A high quality value correspondsto a greater number of detections. The MTDtracker uses a target's qualityvalue as one ofthecriteria in deciding whether the target should beignored, entered to update a track. or pursued toinitiate a new track during the next scan.

The ASR-9 design enhances azimuth resolu­tion by employing a beam-matching algo­rithm. When a run of reports extends beyondtwo beamwidths. ASR-9 compares the ampli­tude data with a pattern that a large singletarget would produce. A substantial differ­ence between the amplitude data and theexpected pattern implies the existence of twotargets in close azimuthal proximity [IJ.

368

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Fig. 5-Targets are grouped in accordance with their spa­tial adjacency. The centroids of the target groups are thencalculated and plotted (shown as xs).

Area Thresholding

The sensitivity of MTD-II permits the detec­tion of birds and insect targets that have meancross sections of approximately 0.003 m 2 andeffective radar-backscattering cross sections assmall as 0.001 m 2

. In comparison, aircraft tar­gets have apparent mean cross sections of 1 m 2

.

Figure 6 gives an example of the distributions ofthese two types of populations, as observed inBurlington. Vt. [I2J. In the figure. the two popu­lation types in the region between -10 dBsm ando dBsm overlap. Because of the overlap. it isimpossible to determine uneqUivocally whethera single report is due to an aircraft or a bird onthe basis of amplitude information only.

The area-thresholding process reduces theeffects of bird populations by limiting the false­alarm rate to a fixed maximum value that has assmall an effect on the detection rate as possible.The threshold is set by integrating reports for thetime necessary to obtain an accurate estimate oflow cross-section target detections. If the countexceeds a nominal value of 60 false alarms perscan over the coverage area. the area-threshold­ing processor raises the thresholds.

The tendency of bird flocks to take to the air

TIle Lincoln Laboratory Journal. Volume 2, Number 3 (1989)

I

en masse and our desire to accumulate repre­sentative and stable target statistics require theuse of two filters in MTD-ll's area-thresholdingprocessor. The first filter integrates over 200 swith approximately 16 mi2 x 3-Doppler-bin reso­lution. The second filter integrates over 5 s andcovers within 20 mi of the radar and within 3Doppler bins. The two-filter combination miti­gates, on a localized basis, the effects of long­lasting bird flights. At the same time, the filtercombination can respond quickly to cope withthe sudden flight of a flock of birds. Figure 7(a)and (b) give an example of the effectiveness ofMTD-ll's adaptive thresholding in coping withechoes from birds. Figure 7(a) gives an exampleof bird echoes that were observed prior to areathresholding. The effectiveness ofMTD-II's areathresholding in coping with bird echoes is illus­trated in Fig. 7(b).

Scan-to-Scan Correlation (Tracking)

Targets that pass the area-thresholding crite­ria are then subjected to a tracking filter. The

Stone et aI. - Advances in Primary-Radar Technology

tracking filter removes those targets or falsealarms which do not have a scan-to-scan re­lationship appropriate to the projectedposition of an aircraft target.

The tracking algorithm initially associates atrack with a target on the basis of the target'snormalized error distance from its predictedposition. Targets associated for two scans aretransmitted to the display. The quality valuecarried by a target report is used to determinethe amount of smoothing done by the tracker'sazimuth-predicting algorithm. After three con­secutive scans, a track that is not matched witha target is dropped. Unmatched targets areretained for one scan so that they can helpinitiate new tracks. Although the tracking pro­cessor does not place a low-velocity limit on thetracks, MTD-II suppresses targets that correlatewith tracks but that never move more than0.25 mi from their initial track positions. Thisfeature is optional in ASR-9.

The result of MTD-ll's overall surveillanceprocessing is the generation ofoutput reports onmore than 98% of aircraft-target detectionswhile the processing limits the false-alarm rateto less than one false alarm per scan undernominal conditions.

Fig. 6-Cross-section population densities for aircraft andbirds (Burlington, Vt.). There is an overlap of the twopopulations in the region between -10 and 0 dBsm.

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Performance

In 1975 a hard-wired version of MTD wasevaluated at the FAA Test Center in AtlanticCity, N.J. The tests demonstrated the efficacy ofthe MTD concept but led to the conclusion thata programmable processor was necessary tofacilitate maintenance and the adjustment ofsite-variable parameters. (The parameters arereqUired to mitigate the effects of site-specificconditions that lead to false alarms, e.g., birdclutter, road traffic, and the presence ofphysicalobjects such as buildings and hills.) Conse­quently, a PMP-based version, the MTD-II, wasassembled and tested at two locations: the FAATest Center, which presented a challengingbird-clutter environment; and the site at theBurlington, Vt., airport, which provided ex­tremely high clutter conditions. Subsequently,Westinghouse Electric Corp., under contract tothe FAA, manufactured the ASR-9, which uti-

The Lincoln Laboratory Journal. Volume 2. Number 3 (1989) 369

Stone et aI. - Advances in Primary-Radar Technology

\' \

-60

60

~ 20

'0.c15 0z'E.s -20

-40

40

60

ofBurlington. Figure 8(a) shows the cumulativereports before MTD tracker processing and Fig.8(b) shows the same data after tracker process­ing. The false-alarm rate was typically less thanone per scan and rose to less than 10 per scanunder adverse conditions. e.g.. W7kS of

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Fig. 7- Bird-echo processing. (a) Radar data before areathresholding. (b) Area thresholding removes undesirablebird echoes. The plots each represent an area of 20 nmiby20nmi.

lizes contemporary signal processing technolo­gy and a special-purpose tracking processorthat was derived from the PMP. The salientresults of Lincoln Laboratory tests of MTD andWestinghouse tests of ASR-9 follow.

Figure 8 gives an example of MTD perform­ance in the intense ground-clutter environment

Fig. 8-An example of the tracker-processor stage ofMTO-II. (a) Cumulative reports before tracker processing.The 1DO-scan plot, which constitutes eight minutes ofradar data, illustrates the typical traffic present at theBurlington, Vt., airport. (b) Cumulative reports after trackerprocessing. MTO-II was able to achieve a false-alarm rateof less than one false alarm per scan. Under adverseconditions, a rate of less than 10 false alarms per scan isachievable.

370 The Lincoln Laboratory Journal. Volume 2. Number 3 (1989)

Stone et aI. - Advances in Primary-Radar Technology

birds were visible.Figure 9 presents the tracker record ofa small

general-aviation aircraft whose backscatteringcross section ranged from -3 dBsm to +8 dBsm[10]. The aircraft deliberately flew over large am­plitude clutter to the southeast of Burlington, aregion where clutter in range cells that exceeded70 dB existed. Under such adverse conditions,MTD could not detect the target because oflimitations imposed by the radar system stabil­ity. For traffic normally encountered in the area,however, the system's detection of targets wasgreater than 94%.

The one-standard-deviation azimuth error ofMTD-II as well as ofASR-9 was measured to be0.13°. The one-standard-deviation range errorwas measured to be 100 ft [12].

The first production model of ASR-9 wasinstalled at Huntsville, Ala. The system, whichhas undergone extensive site adaptation andperformance evaluation, was commissioned

into operational service on 2 May 1989. TheHuntsville site has a relatively benign ground­clutter environment. However, the location ofthe site is such that ground vehicular trafficfrom a number ofroads is visible to the radar. Asa result, maps of the visible roads had to begenerated so that ASR-9 could use the informa­tion in editing the radar data.

The performance of the Huntsville ASR-9represents a quantum improvement over exist­ing digital radar target-detection systems. Fig­ure la, a plot of the output ofASR-9 for a periodof about three minutes, includes the targetdetections of the Air Traffic Control Radar Bea­con System (ATCRBS) for the same time period.As can be seen from the figure, the two systemshave different strengths. Due to its elevation­beam pattern, ASR-9 is prone to losing targets athigh elevation angles (> 45°) and short ranges« 2 nmi). At longer ranges, however, ASR-9 canin many cases exceed the detection probability

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Fig. 9-(a) Hills surrounding the airport in Burlington, Vt., result in intense groundclutter. (b)The trackeroutput, obtainedfrom a Cessna-1 72 flight test taken in the vicinity, demonstratesMTD-I/'s high probability of detection in a challenging environment. The probabilitydetection for the 1-h track of the 3-dBsm target was 0.94.

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Stone et aI. - Advances in Primary-Radar Technology

of the beacon system, particularly in situationsin which an aircraft's beacon antenna isshielded from interrogation.

Figure 10, which shows the ASR-9 operatingwith a false-alarm rate at or better than thesystem's designed rate of 1 false alarm per4.7-s radar scan, demonstrates a target-detec­tion capability on the same order as the beaconsystem. That is, dUring the test ASR-9 had adetection probability that exceeded 95% for theaircraft in the nominal coverage region. Becauseof ASR-9's low false-alarm rate, the integrationofprimary and beacon sensors is possible. Suchintegration provides near-perfect target-detec­tion performance.

However, nominal conditions for radar obser­vation do not occur every day. For example,environmental variables such as anomalousradar propagation due to extremes in the verti­cal atmospheric temperature and moistureprofiles do occur. Small-scale weather echoes

Fig. to-The performance of the Huntsville, Ala., ASR-9radar as compared to the transponder-based Air TrafficControl Radar Beacon System (A TCRBS). This figurepresents 30 radar scans ofdata. Targets detected by bothASR-9 andATCRBS are plotted in green, targets detectedonly by ASR-9 are shown in yellow, and targets detectedonly by ATCRBS are depicted in red. Range rings aredrawn at t O-nmi intervals.

372

also contribute to the number of false targetreports. The ASR-9 radar, which is designedto adapt to difficult environments, should pro­duce no more than 10 false reports per scaneven under extreme conditions. To date, experi­ence in Huntsville has supported this level ofperformance.

Weather Channel

A digital weather channel in ASR-9 supplantsthe wideband-video qualitative rendering ofstorm intensity that existed in the earlier airportprimary radars. The weather channel providessuperior performance by producing smooth,stable contours of storm intensity. Unlike theweather data produced by MTI, the ASR-9 con­tours are not biased by the following factors: thesensor's circuitry, circular polarization, an­tenna high-low beam selection, and sensitivitytime control. In ASR-9, a programmable range­dependent threshold compensates for the abovefactors and reduces the estimate bias that oc­curs from the partial filling of the radar beam bythe vertical extent of the storm. A set of fourfilters effectively eliminates ground clutter. Theattenuating effect of these filters on storm ech­oes that have low radial velocities is mitigated bya ground-clutter map that was made on a clearday. The clear-day map can be used to select, ona range-cell-by-range-cell basis, the output ofthe least attenuating filter for each desiredweather level. Spatial and temporal smoothingprovides stable contours of precipitation re­gions. Abriefdescription ofthe major functionalmodules follows.

Figure 11 contains a block diagram of theASR-9 weather processor. (Details ofthe proces­sor's antenna, the RF switching of the receivedsignal from the high and low antenna beam, andthe selection of linear vertical or circular polari­zation have been omitted.) Digitized quadraturevideo signals pass through four parallel clutterfilters: one all-pass and three notch type. Thefilters are designed to remove scan-modulatedclutter that has an intensity ranging from 12 dBto 49 dB. For that range of clutter intensity, theblock-staggered PRF of the ASR-9 provides forthe processing of8 or 10 pulses to produce filters

The Lincoln Laboratory Journal, Volume 2. Number 3 (1989)

Stone et a1. - Advances in Primary-Radar Technology

PrimitiveDetections

"ClutterFilterBank

Clear-DayClutterMap

Smoothingand

Contouring

ThresholdMemory

Fig. ff-Block diagram of the ASR-9 weatherprocessor, whose outputisa narrowband data stream capable of transmissions via telephone lines.

that have rejection bands centered on zero andfalling between 2 m/s and 7 m/s. To choose theleast-attenuating filterfor each cell, the weatherprocessor uses both the echo-intensity andground-clutter map data. The all-pass filter isselected for clutter-free regions or for regions ofhigh-level weather intensity.

The weather processor then subjects thefiltered output from each cell to thresholdsthat are referenced to the six National WeatherService (NWS) levels [13-15] of Table 2. Thethresholds are adjusted to compensate for dif­ferent factors such as range dependence, beamfilling [I, 14], polarization, and high-low beam[14,15].

Rapid scanning of the radar antenna and/orfluctuations of the weather echoes can lead tonoisy storm-intensity estimates for a singleresolution cell. Therefore, the single-cell thresh­old crossings are smoothed over 1 nmi and thehighest level of 8 of the 16 resolution cells ispassed on for further temporal and spatialsmoothing. Six consecutive antenna scans aremedian filtered to provide temporal smoothing.Spatial smoothing is carried out on two levels.The first is carried over adjacent echo clusters;the second expands the weather contoursslightly to ensure that small regions of intensereflectivity will not be obscured on the control­ler's display.

The Lincoln Laboratory Journal. Volume 2, Number 3 (1989)

The performance of the weather channel hasundergone simulation analysis, emulation, andin situ validation. The simulation analysis byM.E. Weber [13] showed that under a variety ofmeteorological conditions, the weather channelprovides accurate representation of the NWSlevel. In addition, Weber demonstrated that thebroad range ofintensities encompassed by eachof the six levels would lead to an accuracy ofmost of the estimates to within one NWS level.

The emulation facility (FL-3) developed forthe investigation of wind shear [16] was usedto acquire time-series data that were processedby the algorithms described above. When theweather channel of the first ASR-9 was checkedagainst observations made by both the emula­tion-facility radar and a pencil-beam Dopplerweather radar, we found that the channel pro­vided appropriate representations of storm in­tensity for a variety of storms.

Figure 12, a time-lapse plot ofdata generatedby the ASR-9 weather channel, shows the pro­gression of a squall line. Five of the six NWSlevels occurred in the storm.

The ASR-9 weather data appear on the airtraffic controller's display in either a discrete(Fig. 13[a]) or summation (Fig. 13[b]) mode. Bothmodes and ASR-9's six-level-selection featuresprovide air traffic controllers with accurate andtimely weather information that can be used to

373

Stone et aI. -Advances in Primary-Radar Technology

Table 2. National Weather Service (NWS) Levels

NWS dBz RainfallLevel Range Category

1 16 to 30 Mist to light2 30 to 41 Moderate3 41 to 46 Heavy4 46 to 50 Very heavy5 50 to 56 Intense6 >56 Extreme (hail)

(

manage the traffic flow to gate posts, which aretypically 40 mi from an airport. The features arealso helpful in effecting tactical control of air­craft arrivals and departures in the presence ofhazardous weather [14].

System Improvements

The original design concept, embodied inMTD-II, did not provide for the elimination ofrange-ambiguous aircraft echoes, Le., aircraftflYing within the detection capability ofthe radarbut beyond the unambiguous range. This short­coming resulted from a design decision to elimi­nate range-ambiguous fixed clutter. Anotherproblem may arise when nearby automobiletraffic is present. The following sections describecorrective measures that have been imple­mented or proposed.

Range-Ambiguous Targets

The problem of detecting range-ambiguousaircraft was solved in ASR-9 by applYing mi­crostagger to the pulse-repetition interval.Microstagger increases the pulse-repetitioninterval by two range cells (300 m) so thatechoes from the first and subsequent ambigu­ous-range intervals are asynchronous with oneanother. By using this asynchronization, we caneliminate the range-ambiguous echoes of theaircraft.

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Figure 14(a} is an example ofrange-ambigu­ous echoes. Note that the echoes (shown inmagenta) produce nearly radial tracks that re­sult from the extended azimuthal coverage oftheradar beam. Figure 14(b} shows how mi­crostagger can effectively remove range­ambiguous echoes. In mountainous regionswhere range-ambiguous clutter can occur, itmay be necessary to revert to a nonstagger-

Fig. 12-ASR-9 weather-channel output showing the pro­gression of a squall line. Color is used to denote the sixNational Weather Service (NWS) levels of Table 2. Notethat five of the six levels were present in the storm.

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Fig. 13-ASR-9 weather reports as displayed by the Auto­mated Radar Terminal System (ARTS). An air traffic con­troller can select either the (top) discrete or (bottom) sum­mation mode to obtain a comprehensive plan view of theweather situation.

ed pulse-repetition interval in order to eliminatethe clutter. An extended clutter map will aid theselection of the appropriate signaling strategy.

Vehicular Traffic

The ASR-9 radar has a subclutter visibility ofabout 45 dB; Le., the radar can detect a movingtarget with an amplitude about 45 dB less thanthe amplitude of the ground clutter returns inthe same range-azimuth cell. However, high

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subclutter visibility is often more of a problemthan a benefit in controlling the false-alarm rate.A striking example of this effect occurs whenautomobiles and other ground traffic are pres-

Fig. 14-(top) Tracks ofrange-ambiguous aircraftdetectedwith constant-pulse-repetition-frequency (PRF) blocks.The magenta markings indicate targets that have beendetected in only one of the two radar PRFs. Most of thesetargets are false alarms caused by echoes received fromaircraftatgreater than the 60-nmi instrumented range oftheradar. (bottom) The range-ambiguous echoes have beeneliminated with microstagger.

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ent. When roads are visible, air traffic control­lers using current radars are aware that sometarget reports may result from ground vehicles.Between the limited subclutter visibility of cur­rent radars and the lack of automated targetdetection and tracking, these returns are usu­ally considered to be relatively minor annoy­ances rather than a significant limitation onsystem performance. In the case of new high­performance radars. the situation becomesmore critical.

The increased subclutter visibility of theASR-9 leads to the detection of surface vehicleswithin the line of sight of the radar. In fact. oneaspect of most of the class of false alarmsuncovered by the new signal processing technol­ogy is that. with the exception of bird-targetreports. the false alarms are produced by scat­terers on the ground. The presence of birdreports can be identified through the careful

Fig. 15-A five-scan plot of the short-range-detection andfalse-alarm-rate performance of ASR-9 in Huntsville, Ala.This plotshows on an expandedrange scale the same dataas the first five scans of Fig. 10. (Targets detected by bothASR-9 andATCRBS are plotted in green, targets detectedonly by ASR-9 are shown in chartreuse, and targets de­tected only byATCRBS are depicted in orange.) In ASR-9,false alarms are removed with interference detection, fixedsite-dependent censoring maps, adaptive amplitudethresholding, and scan-to-scan correlation.

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Fig. 16-A simulation of the false-alarm environment atHuntsville, Ala., for the same period as Fig. 15. Thissimulation was performed with data taken by the LincolnLaboratory FL-3 test radar, whose site was about 0.5 nmifrom the ASR-9. The use ofthe FL -3 data allows a depictionof the expected false-alarm rate without automatic false­alarm removal techniques.

assessment of target-amplitude statistics.However, this technique is not effective againstground targets such as trucks that elicit targetreports that have both amplitudes and Dopplerfrequencies comparable to those of aircraft.

To date, MTD-II and the ASR-9 algorithmshave been capable in controlling false alarmsdue to ground traffic (Fig. 15). Before the data ofFig. 15 were subjected to postprocessing, therewere more than 100 false reports per scan. Thefalse reports were removed with a site-specificmap. which contained information about visibleroads.

Figure 16 is a reproduction ofthe results ofanASR signal processor simulation. (The data aretaken from wind-shear experiments with theLincoln Laboratory FL-3 radar [17]. which is amodified ASR-8 radar used for the developmentof ASR signal processing algorithms.) We pro­cessed the recorded time-series data to simulatethe performance ofan MTD-like processor in thesame environment and time period as the con-

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ditions under which the ASR-9 data shown inFig. 15 were collected. (To highlight the vehicu­lar traffic, we used only the first 20 nmi ofthe data.) Fig. 16 exhibits a large number offalse-target reports, many of which come fromautomobile and truck traffic. In the ASR-9 plot(Fig. 15), these reports were removed at thesignal processor level by a site-dependent tar­get-censoring map that was carefully handcompiled to screen those roads which are visibleto the radar.

We should point out that Huntsville is farfrom an extreme case with respect to vehiculartraffic. Hence this technique will be furthertested as ASR-9 installations proceed at otherairports. Whether the use of target-censoringmaps will prove acceptable at all sites remainsquestionable. The possibility exists that at somesites important aircraft-coverage regions mightoccur over dense ground-traffic areas. This situ­ation would prevent the Simultaneous achieve­ment of both a very low false-alarm rate and anacceptable probability of detection.

Thus it is desirable to deal with the problemofautomobile traffic in a more fundamental way.One approach under evaluation is the additionof a Single-target height-measurement capa­bility to the radar. This approach places tar­gets that are due to ground-based returns intoelevation-angle classes that can be suppressedwithout any degradation to the aircraft­detection ability of the system.

In Huntsville we began to explore the use ofelevation angles to differentiate betweenground-based and airborne targets. We investi­gated whether a vertical interferometer consist­ing of two radar receiving feed horns couldaccurately measure the elevation angles.

The ASR-8 and ASR-9 radars have two feedhorns mounted on rotating antennas. The feedhorn associated with the lower beam is alwaysused to transmit, and either ofthe two feeds canbe used for reception. In normal operation thereceiver is simply range switched between thetwo horns. The higher-beam horn is used atshorter ranges to provide about 12 db of addi­tional ground-clutter rejection. The lower-beamhorn is used at longer ranges (Le., at rangesgreater than about 12 nmi) in which the low-

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angle coverage is more important.In contrast to the configuration used in the

ASR-8 and ASR-9, the FL-3 radar has two sepa­rate receiver chains and can thus record videosimultaneously from both antenna feeds. Thesimultaneous signals can be used to deter­mine a target's elevation in the following way.By considering the complex cross-spectrumof the two time series, we can take the cross­spectral phase at a particular frequency to berepresentative of the elevation of a targetat that frequency, even in the presence ofground clutter or other targets with differentvelocities.

Figure 17 shows an example of the vertical­amplitude and phase-pattern measurements ofthe ASR-9 antenna. As might be expected, therelationship between the differential phasevalue and the elevation angle of the scatterer isgenerally monotonic. The slope of the differen­tial phase curve is steepest at low elevationangles, and since the height-assignment accu­racy of such a processor increases with increas­ing phase slope, the antenna should be capableof making accurate elevation-angle measure­ments of objects near the ground. For highsignal-to-noise targets (20 to 30 dB) with theASR-9 antenna, this accuracy should be betterthan ± 0.1 0 at low elevation angles.

The vertical-interferometer approach isbasically a vertical-phase monopulse system.Consequently, the approach shares many ofthedrawbacks common to such systems-in par­ticular, problems with the phase stability ofsuch RF hardware as waveguides and rotaryjoints.

On the other hand, an important advantage ofthe vertical-interferometer approach is that itprovides a means of identifying the receivedsignal from the ground clutter itself. As the radarcomponents drift slowly in time, the ground­clutter signal supplies a reference phase at eachrange and azimuth that can be tracked. Thisdynamic approach to obtaining a referencephase is also useful since it automatically ac­counts for variations in ground topographyaround the radar (Fig. 18).

We can design a radar processor so that itsalgorithms for signal processor thresholding

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Stone et aI. - Advances in Primary-Radar Technology

0 180

-10 90

en OiQ)

~ 0~

c -20 Q)

'ro CJl

Low Beam ellCJ

~~

a..

-30High Beam -90

Differential Phase

-180-40

-10 0 10 20 30 40

Elevation Angle (deg)

Fig. 17-Vertical amplitude andphase pattern ofa production ASR-9 antenna. (The datawere measured by Westinghouse Electric Corp. under contract to the FAA.)

select only those range-azimuth-Dopplerthreshold crossings which have a dual-beamcross-spectral phase that is not within someerror tolerance ofthe local ground-return phase.Figure 19 shows an example ofthe simulation ofsuch a processor from the FL-3 data set. Thetarget plot demonstrates a greater than 90%reduction of false targets while it preserves thedetection of nearly all of the genuine aircraftreturns.

The results of the simulation demonstratethat with some increase in RF and signal pro­cessing complexity, vehicular traffic can beautomatically eliminated with far less site-spe­cific knowledge than was required by theground-clutter-map method. The technique canalso be extended to zero Doppler velocity inwhich, in superclutter conditions, the targetsignal is stronger than the clutter signal. Underthese circumstances, the vertical-interfero­meter technique can provide better visibilitythan the zero-Doppler temporal CFAR thresh­olding currently employed.

Although the discussion in this article hasconcentrated on false alarms due to ground ve­hicles, the same processing strategy can poten­tially be used to remove false reports that resultfrom finite-velocity clutter such as wipdblownvegetation.

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Summary

MTD and its implementation in the produc­tion ASR-9 represent a significant advance in

Fig. 18-A plot showing the apparent elevation angle ofvisible ground clutter as computed from the phase mea­sured by the two vertical beams that were used as aninterferometer. In this plot, the phase increases from therelatively large depression angle near the 60-ft FL -3 tower(note the blue colors) to higher elevation angles (shown inyellow) at longer ranges. The cross-spectralphase rangesfrom 0° (indicated by blue) to 100° (indicated by yellow).

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Fig. 19-0utputof the FL-3-basedASR emulation system.(The data are from Fig. 16.) Note that false alarms due tointerference by other radars (chartreuse), bird echoes(red), andground vehicular traffic (orange) have been de­tected. Bird echoes are removed with area thresholding.Clutter resulting from surface vehicular traffic is removedwith a phase-derived height estimate. Targets that surviveall of the false-alarm tests are shown in green.

the surveillance of aircraft and weather that isrequired to support the automation ofair trafficcontrol. The low false-alarm rate of MTD's air­craft-detection algorithm can be improved fur­ther by adding the elevation-angle discriminantto reject ground traffic. A wind-shear detectioncapability that could also be incorporated toprovide an at-the-airport measurement of haz­ardous radial wind fields is an additional topic ofcurrent investigation. In summary, the MTDand its enhancements will effectively serve in thefuture as the processing architecture formechanically scanning airport primary radars.

Acknowledgments

We are indebted to C.E. Muehe, who sug­gested the MTD concept and led the develop­ment team that produced the first-generationsystem. Muehe was also responsible for thearchitecture of the parallel microprogrammedprocessor that was the major novel componentof the second-generation MTD. We also ac-

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Stone et aI. - Advances in Primary-Radar Technology

knowledge our Lincoln Laboratory colleagueswho made many valuable, creative contribu­tions, and constructed, programmed, andtested the MTD systems. The participation ofFAA personnel in the evaluation of the MTDconcept is appreciated. Furthermore, we ac­knowledge the contributions of the late DavidKarp, whose important refinements to the sys­tem and careful assessment of its performancewere invaluable.

We acknowledge the support of our FAAsponsors, Martin Pozesky, Deputy AssociateAdministrator for National Airspace SystemDevelopment, and Carmine Primeggia, ASR-9Program Manager.

References

1. J .w. Taylor, Jr. and G. Brunins, "Design ofa NewAirportSurveillance Radar (ASR-9)," Proceedings oj IEEE 73,284(1985).

2. C.E. Muehe, Jr. and L. Cartledge. "A High Performance,Low Cost. Air Traffic Control Radar." Technical Note1973-12. Lincoln Laboratory (15 Feb. 1973),AD759179.

3. C.E. Muehe. "Concepts for Improvement ofAirport Sur­veillance Radars," Project Report ATC-14, Lincoln Labo­ratory (26 Feb. 1973), AD75739.

4. C.E. Muehe, L. Cartledge, W.H. Drury, E.M. Hofstetter,M. Labitt, P.B. McConson. and V.J. Sferrino, "NewTechniques Applied to Air Traffic Control Radars," Pro­ceedings ojlEEE62. 716 (June 1974).

5. "Doppler ProcessingWaveform Design and PerformanceMeasures for Some Pulsed Doppler and MTD Radars,"Ortung und Navigation Part 1, p. 417 (Mar. 1981); Part2.p. 2 (Jan. 1982).

6. W.H. Drury, "Improved MTI Radar Signal Processor."ProjectReportATC-39, Lincoln Laboratory (3 Apr. 1975).FAA-RD-74-185.

7. C.E. Muehe, "Digital Signal Processor for Air TrafficControl Radars," lEEE/NEREM 1974, Part 4: RadarSystemsandCoponents, Boston, 28-31 Oct. 1974. p. 73.

8. C.E. Muehe, P.G. McHugh. W.H. Drury, and B.G. Laird,"The Parallel Microprogrammed Processor (PMP)," lEE1977 IntL RadarConj, London, 25-28 Oct. 1977, p. 97.

9. C.E. Muehe. "Advances in Radar Signal Processing,"lEEE ELECTRO /74 ProjessionalProgram. Boston. 11-14May 1976, p. 1.

10.J.R. Anderson and D. Karp, "Evaluation of the MTD in aHigh-Clutter Environment." IEEE 1980 InternationalRadar Coriference, Arlington. VA, 28-30 Apr. 1980, p.219.

11. "Airport Surveillance Radar (ASR-9), " Department ojTransportation/ Federal Aviation AdministrationSpecljlcation (l Oct. 1986), FAA-E-2704B.

12.D. Karp and J.R. Anderson, "Moving Target Detector(Mod II) Summary Report." Project Report ATC-95. lin­coln Laboratory (3 Nov. 1981), ADAl14709.

13.M.E. Weber, "Assessment of ASR-9 Weather ChannelPerformance: AnalySiS and Simulation," Project ReportATC-138, Lincoln Laboratory (31 July 1987), FAA/PM­86-16.

14.D.C. Puzzo. S.W. Troxel. M.A. Meister, M.E. Weber, andJ.V. Pieronek. "ASR-9 Weather Channel Test Report."

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ProjectReportATC-165. Lincoln Laboratory (1989). FAA­PM-86-38.

15.S.W. Troxel. "ASR-9 Weather Channel Test Report.Executive Summary," Project Report ATC-168, LincolnLaboratory (3 May 1989). DOT/FAA/PS-89/6.

16.M.E. Weber and T. Noyes. "Wind Shear Detection with

MELVIN L. STONE is theAssociate Group Leader ofthe Air Traffic SurveillanceGroup. which develops tech­nology for current and next­

generation airport-surveillance radars (ASR) and airportsurface detection equipment (ASDE). Mel received a B.S.degree in electrical engineering from MIT in 1951. He partici­pated in the development ofweather radar techniques as amember of the staffof the MIT Dept. of Meterology WeatherRadar Laboratory from 1948 to 1951. Since he joined lin­coln Laboratory 37 years ago, Mel's research interests haveincluded weather radar, HF ground-wave backscatter fromthe sea and aircraft. lunar albedo at UHF. auroral backscat­ter from UHF through L-band. and ionospheric effectscaused by burning missiles. He developed a 400-kWX-band radar used in the Fourth Test ofGeneral Relativity.Mel was also leader of the group that developed an air-to­ground mOving-target radar. the progenitor of the U.S. AirForce/Army Joint Standoff Target Attack RadarSystem (JSTARS). He is a member of the IEEE, AGU. SigmaXi, and Eta Kappa Nu.

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Airport Surveillance Radars." LincolnLaboratoryJoumal2,511 (1989).

17.M.E Weber and T.A. Noyes. "Low Altitude Wind ShearDetection with Airport Surveillance Radars: Evaluationof 1987 Field Measurements," Project Report ATC-159.Lincoln Laboratory (31 Aug. 1988), FAA/PS-88/ 10.

JOHN R. ANDERSON is anassociate professor of theDepartment of Meteorologyand associate director of theSpace Science and Engi­

neering Center at the University of Wisconsin in Madison.The system engineer for the MID-II radar. John has beeninvolved in the development of radar signal and data pro­cessing algOrithms. He is currently involved in the develop­ment of signal processing and post-processing algorithmsfor Doppler weather radars designed for the detection ofthunderstorm-generated aviation hazards. His meteorologi­cal research projects include the study of the dynamiCS ofthe tropical atmosphere and the extension of 4-D data­assimilation techniques to the problem of integrating Dop­pler radar data with thunderstorm-scale prediction modelsfor the purpose of short-term forecasts of aviation hazardsnear airports. John received a S.B. in physics and S.M.in meteorology from MIT in 1976 and 1982, respectively.and a Ph.D. in atmospheric sciences from Colorado StateUniversity in 1984.

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