Tài liệu Digital Signal Processing Handbook P33 docx

Clay Stewart. “Synthetic Aperture Radar Algorithms.” 2000 CRC Press LLC. <http://www.engnetbase.com>. SyntheticApertureRadar Algorithms ClayStewart ScienceApplicationsInternational Corporation VicLarson ScienceApplicationsInternational Corporation 33.1Introduction 33.2ImageFormation Side-LookingAirborneRadar(SLAR) • UnfocusedSynthetic ApertureRadar • FocusedSyntheticApertureRadar 33.3SARImageEnhancement 33.4AutomaticObjectDetectionandClassificationinSAR Imagery References FurtherReadingandOpenResearchIssues 33.1 Introduction Asyntheticapertureradar(SAR)isaradarsensorthatprovidesazimuthresolutionsuperiortothat achievablewithitsrealbeambysynthesizingalongapertureusingplatformmotion.Thegeometryfor theproductionoftheSARimageisshowninFig.33.1.TheSARisusedtogenerateanelectromagnetic mapofthesurfaceoftheearthfromanairborneorspaceborneplatform.Thiselectromagneticmap ofthesurfacecontainsinformationthatcanbeusedtodistinguishdifferenttypesofobjectsthatmake upthesurface.Thesensoriscalledasyntheticapertureradarbecauseasyntheticapertureisusedto achievethenarrowbeamwidthnecessarytogetahighcross-rangeresolution.InSARimagerythe twodimensionsarerange(perpendiculartothesensor)andcross-range(paralleltothesensor).The rangeresolutionisachievedusingahighbandwidthpulsedwaveform.Thecross-rangeresolution isachievedbymakinguseoftheforwardmotionoftheradarplatformtosynthesizealongaperture givinganarrowbeamwidthandhighcross-rangeresolution.Thepulsereturnscollectedalongthis syntheticaperturearecoherentlycombinedtocreatethehighcross-rangeresolutionimage.ASAR sensorisadvantageouscomparedtoanopticalsensorbecauseitcanoperatedayandnightthrough clouds,fog,andrain,aswellasatverylongranges.Atverylownominaloperatingfrequencies,less than1GHz,theradarevenpenetratesfoliageandcanimageobjectsbelowthetreecanopy.The resolutionofaSARgroundmapisalsonotfundamentallylimitedbytherangefromthesensorto theground.Ifagivenresolutionisdesiredatalongerrange,thesyntheticaperturecansimplybe madelongertoachievethedesiredcross-rangeresolution. ASARimagemaycontain“speckle”orcoherentnoisebecauseitresultsfromcoherentprocessingof thedata.ThisspecklenoiseisacommoncharacteristicofhighfrequencySARimageryandreducing speckle,orbuildingalgorithmsthatminimizespeckle,isamajorpartofprocessingSARimagery beyondtheimageformationstage.Traditionaltechniquesaveragedtheintensityofadjacentpixels, resultinginasmootherbutlowerresolutionimage.AdvancedSARsensorscancollectmultiple polarimetricand/orfrequencychannelswhereeachchannelcontainsuniqueinformationaboutthe c  1999byCRCPressLLC FIGURE 33.1: SAR imaging geometry. surface. Recent systems have also used elevation angle diversity to produce 3-D SAR images using interferometric techniques. In all of these techniques, some sort of averaging is employed to reduce the speckle. The largestconsumersof SARsensors andproducts are thedefense andintelligencecommunities. These communities use SAR to locate and target relocatable and fixed objects. Manmade objects, especially ones with sharp corners, have very bright signals in SAR imagery, making these objects particularlyeasytolocatewithaSARsensor. AtechnologysimilartoSARisinversesyntheticaperture radar (ISAR) which employs motion of the platform to image the target in cross-range. The ISAR data can be collected from a fixed radar platform since the target motion creates the viewing angle diversitynecessaryto achieve a given cross-range resolution. ISAR systems have been used to image ships, aircraft, and ground vehicles. InadditiontothedefenseandintelligenceapplicationsofSAR,thereareseveralcommercialremote sensing applications. Because aSARsensor can operate day and night and in all weather, it provides the ability to collect data atregular intervals uninterrupted by natural influences. This stable source of ground mapping information is invaluable in tracking agriculture and other natural resources. SAR sensors have also been used to track oil spills (oil-coated water has a different backscatter than natural water), image underground rock formations (at some frequencies the radar will penetrate some soils), track ice conditions in the Arctic, and collect digital terrain elevation data. RadarisanabbreviationforRAdio DetectionAndRanging. Radarwasdevelopedinthe1930s and 1940s to detect and track ships and aircraft. These surveillance and tracking radars were designed so that a target was contained in a single resolution cell. The size of the resolution cell was a critical design parameter. Smaller resolution cells allowed one to determine the location of a target more accurately and increased the target-to-clutter ratio, improving the ability to detect a target. In the c  1999 by CRC Press LLC 1950s it was observed that one could map the ground (an extended target that takes up more than oneresolution cell) by mountingthe radaron thesideof anaircraft andbuildinga surface mapfrom the radar returns. High range resolution was achieved by using a short pulse or high bandwidth waveform. The cross-range resolution was limited by the size of the antenna, with the cross-range resolution roughly proportional to R/L a where R is the range from the sensor to the ground and L a is the length of the antenna. The physical length of the antenna was constrained, limiting the resolution. In 1951,CarlWileyof theGoodyearAircraftCorporation noted thatthereflections from twofixedtargetsin theantennabeam, butatdifferentangular positionsrelative tothevelocityvector of the platform, could be resolved by frequency analysis of the along track (or cross-range) signal spectrum. Wiley simplyobservedthateachtarget haddifferentDopplercharacteristics becauseofits relative positionto ther adarplatformand that onecouldexploit theDoppler tosepar ate thetargets. The Doppler effect is, of course, the change in frequency of a signal transmitted or received from a moving platform discovered by Christian J. Doppler in 1853: f d = ν/λ where f d is the Doppler shift, ν is the radial velocity between the radar and target, and λ is the radar wavelength. While the Doppler effect had been used in radar processing before the 1950s to separate moving targets from stationary ground clutter, Wiley’s contribution was to discover that with aside lookingairborne radar(SLAR), Dopplercould beusedto improvethe cross-range spatial resolution of the radar. Other early work onSAR was done independentlyof Wiley at the University ofIllinoisandthe UniversityofMichiganduringthe1950s. ThefirstdemonstrationofSARmapping was done in 1953 by the University of Illinois by performing frequency analysis of data collected by a radar operating at a 3-cm wavelength from a C-46 aircraft. Much work has been accomplished perfecting SAR hardware and processing algorithms since the first demonstration. For a much more detailed description of the history of SAR including the development of focused SAR, phase compensation techniques, calibration techniques, and autofocus, see the recent book by Curlander and McDonough[1]. Before offering a brief description of some processing approaches for forming, enhancing, and interpreting SARimagery,we give twoexamples of existing SAR systems andtheir applications. The firstsystemistheShuttleImagingRadar(SIR)developedbytheNASAJetPropulsionLaboratory(JPL) and flown on several space shuttle missions. This system was designed for non-military collection of geographic data. The second example is the Advanced Detection Technology Sensor (ADTS) built by the Loral Corporation for the MIT Lincoln Laboratory. The ADTS sensor was designed to demonstrate the capability of a SAR to detect and classify military targets. Table 33.1 contains the basicparameters fortheADTSand SIRSARsystems alongwithdetailsonseveralother SARsystems. Figure33.2showsanexampleimageformedfromdatacollectedbytheSIRSAR.TheJPLengineers describe this image as follows: ThisisaradarimageofMountRainierinWashingtonstate Thisimagewasacquired by the Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X- SAR) aboard the space shuttle Endeavor on its 20th orbit on October 1, 1994. The area shown in the image is approximately 59 kilometers by 60 kilometers (36.5 miles by 37 miles). North is toward the top left of the image, which was composed by assigning red and green colors to the L-band, horizontally transmitted and vertically received, and the L-band, horizontallytransmitted and vertically received. Blueindicates theC-band, horizontallytransmittedandverticallyreceived. Inadditiontohighlightingtopographic slopes facingthe space shuttle, SIR-C recordsruggedareasas brighter andsmooth areas as darker. The scene was illuminated by the shuttle’s radar from the northwest so that northwest-facing slopes are brighter and southeast-facing slopes are dark. Forested regions are pale green in color; clear cuts and bare ground are bluish or purple; ice is c  1999 by CRC Press LLC TABLE 33.1 Example SARSystems Resolution Swath Platform Bands polarization (m) width Interferometry JPL AIRSAR C, L, P–Full 4 10–18 km Cross track L,C Along track L,C SIR-C/X-SAR C, L–Full,X-VV 30 × 30 15–90 Multi-pass ERIM IFSARE X–HH 2.5 × 0.8 10km Cross track ERIM DCS X–Full < 1 1 km Cross track MIT LL ADTS Ka (33 GHz)–Full 0.33 400 m Multi-pass NORDEN G11 Ku–VV 1,3 5 km 3 Along track 3 Crosstrack Phase centers SRI UWB 100–300 MHz, 1 × 1 400–600 m None FOLPEN 2 200–400 MHz, 300–500 MHz, HH LORAL UHF 500–800MHz, 0.6 × 0.6 280m None MSAR Full NAWC P-3 C, L, X–Full 1.5 × 0.7 5km Along track X,C NAWC P-3 600 MHz–Full 0.33 × 0.66 930 km None UWB Upgrade tunable over 200– 900 MHz Tier II+ UAV X 1 and 0.3 10 km None SAR dark green and white. The round cone at the center of the image is the 14,435-foot (4,399-meter) active volcano, Mount Rainier. On the lower slopes is a zone of rock ridges and rubble (purple to reddish) above coniferous forests (in yellow/green). The westernboundaryofMountRainierNationalParkisseenasatransitionfromprotected, old-growth forest to heavily logged private land, a mosaic of recent clear cuts (bright purple/blue) and partiallyregrown timber plantations (pale blue). Figure 33.3 is an example image collected by the ADTS system. The ADTS system operates at a nominal frequency of 33 GHz and collects fully polarimetric, 1-ft resolution data. This image was formed using the polarimetric whitening filter (PWF) combination of three polar imetric channels toreduce thespeckle noise. Theoutput of thePWF isanestimateof radar backscatter intensity. The image displayed in Fig. 33.3is basedon a falsecolormapwhich mapslowintensity toblack followed by green, yellow, and finally white. The color map simply gives the non-color radar sensor output falsecolorsthatmakethelowintensityshadowslookblack,thegrasslookgreen,thetreeslookyellow, and bright objects look white. This sample image was collected near Stockbridge, New York, and is of ahouse with an above groundswimmingpool andseveral junkedcars in thebackyard. The radar is at the top of the image looking down at a 20 ◦ depression angle. The scene contains large areas of grass or crops and some foliage. Note the bright returns from the manmade objects, including the circular above-ground swimming pool, and strong corner reflector scatteringfrom some of the cars in thebackyard. Also note the relatively strong return from the foliagecanopy. At thisfrequency the radar does not penetrate the foliage canopy. Note the shadows behind the trees where there is no radar illumination. In this chapter on SAR algorithms, we give a brief introduction to the image formation process in Section 33.2. We review a few simple algorithms for reducing speckle noise in SAR imagery and automatic detection of manmade objects in Section 33.3. We rev iew a few simple automatic objectclassification algorithmsfor SARimagery inSection33.4. This briefintroductionto SARonly contains a few example algor ithms. In the Section “Further Reading”, we recommend some starting c  1999 by CRC Press LLC FIGURE 33.2: SAR image of Mt. Rainier in Washington State taken from shuttle imagingra dar. pointsfor further reading onSARalgorithms,and discussseveralopen issuesundercurrentresearch in the SAR community. 33.2 Image Formation In this section, we discuss some basic principles of SAR image formation. For more detailed infor- mation about SAR image formation, the reader is directed to the references given at the end of this chapter. One fundamental scenario under which SAR data is collected is shown in Fig. 33.1.An aircraft flies in a straight path at a constant velocity and collects radar data at a boresight of 90 ◦ .In practice it is impossible foranaircraft to fly in a perfectly straight line at a constant velocity (at least within a wavelength), so motion (phase) compensation of the received radar signal is needed to ac- countfor aircraftperturbations. The radaron theaircraft transmitsa short pulsedwaveform oruses frequency modulation to achieve highrangeresolution imaging of the surface. The pulses collected fromseveralpositionsalongthetrajectoryoftheaircraftarecoherentlycombinedtosynthesizealong synthetic aperture in order to achieve a high cross-range resolution on the surface. In this section, we first discuss SLAR where only range processing is performed. Next, we discuss unfocused SAR where both range and cross-range processing are executed. Finally, we discuss focused SAR where “focusing” is performed inaddition to rangeandcross-range processing to achieve the highestreso- lution and best image quality. At the end of this section we briefly mention several other important c  1999 by CRC Press LLC FIGURE 33.3: SAR image near Stockbridge, New York, collected by the ADTS. SARimageformationtopicssuchasphase compensation, clutter-lock,autofocus,spotlightSAR,and ISAR. The details of these topics can be found in [1]–[3]. 33.2.1 Side-Looking Airborne Radar (SLAR) SLAR is the earliest ra dar system for remote surveillance of a surface. These radar systems could only perform range processing to form the 2-D reflectivity map of the surface, so the cross-range resolution is limited by the real antenna beamwidth. TheseSLAR systems typicallyoperated at high frequencies(microwaveormillimeter-wave)tomaximizethecross-rangeresolution. WecoverSLAR systems because SLAR performs the same range processing as SAR, and the limitations of a SLAR motivate the need for SAR processing. The resolution of a SLAR system is limited by the radarpulse width in the range dimension, and the beamwidth and slant range in the cross-range dimension: δ r = cT /2 cos η δ cr = Rλ/L a wherewe representtheapproximate3-dB beamwidth ofthe antennabyλ/L a ,δ r is therange resolu- tion, δ cr is the cross-range resolution, c is the speed of wave propagation, T is the compressed pulse width, η is the angle between the radar beam and the surface, R is the slant range to the surface, λ is the wavelength, and L a is the length of the antenna. Thegoalistodesign theSLARwithanarrowbeamwidth,shortslantrange,andashort pulsewidth toachievehigh resolution. Inpractice, thepulsewidth oftheradar islimitedbyhardwareconstraints and theamountof“energy ontarget” requiredto getsufficient signal-to-noiseratio to obtaina good c  1999 by CRC Press LLC image. To achieve a high rangeresolution without a short pulse, frequency modulation can be used to synthesize an effectively short pulse. This process of generating a narrow synthetic pulsewidth is called pulse compression. The approach is to introduce a modulation on the transmitted pulse,and then pass the received signal through a filter matched to the transmit signal modulation. The most common transmit waveforms usedfor pulse compression are linearFM (or chirp) andphase coded. Some radars use a digital version of linear FM called a stepped frequency waveform. Weillustrate pulsecompressionwiththe idealapplication of thelinear FM waveform. Thesquare pulse is modulated by a linear FM signal, and the resulting transmit signal is s(t) =    cos  ω 0 † − 1 2 µ† 2  | †|≤T/2 0 | †| >T/2 where the bandwidth (frequency deviation) introduced by the linear FM is f = Tµ/2π Ifthistransmitpulseisperfectly reflectedfromastationarypointtarget, rangelossesareignored,and weshiftintimetoremovethetwo-waydelay;thereceivedsignalisexactlythesameasthetransmitted signal. The matched filter response for the transmitted signal is h(t) =  2µ π  1/2 cos  ω 0 † + 1 2 µ † 2  The output of the received signal applied to the matched filter is: ( †) =  µT 2 2π  1/2 sin ( µT †/2 ) ( µT †/2 ) Re  e j  ω 0 †+ 1 2 µ† 2 +π/4   This output has a mainlobe that has a 4-dB beamwidth of 1/f . The resulting compressed pulse can besignificantlynarrower than thewidthof thetransmitted pulse with apulse compression ratio of Tf. The range resolution of the radar has been increased by this pulse compression factor and is now given by: δ r ≈ c/2f cos η Note that the range resolution in the ideal case is now completely independent of the physical width of thetransmitted pulse. Performing range compression against real radar targets thatDoppler shift the frequency of the receive signal introduces ambiguities resulting in additional signal processing issues thatmust be addressed. Thereis a trade-offbetween the abilityof a radarwaveform to resolve a target in range and frequency. The performance of a waveform in range-frequency space is given by its ambiguity. The ambiguityfunction is the output of the matched filter for the signal for which it is matched and for frequency shifted versions of that signal. The references contain a much more detailed description of ambiguity functions and radar waveform design. Using pulse compression, a SLAR system can achieve a very high range resolution on the order of 1 ft or less, but the cross-range resolution of the SLAR is limited by the physical beamwidth of the antenna, the operating frequency, and the slant range. This cross-range resolution limitation of SLAR motivates the use of a synthetic array antenna to increase the cross-range resolution. 33.2.2 Unfocused Synthetic Aperture Radar Figure 33.1 provides a good geometric description of SAR. As with SLAR, the radar platform moves alongastraightlinecollectingradardatafromthesurface. TheSARsystemgoesonestepfurtherthan c  1999 by CRC Press LLC SLAR by coherently combining pulses collected along the flight path to synthesize a long synthetic array. Thebeamwidthofthissyntheticapertureissignificantlynarrowerthanthephysicalbeamwidth (real beam) of the real antenna. The ideal synthetic beamwidth of this synthetic aperture is θ B = λ/2L θ The factor of two results from the two-way propagation from the movingplatform. The unfocused SARcanbeimplementedbyperformingFFTprocessinginthecross-rangedimensionforthesamples in each range bin. Thisissimply the conventional beamformer for an array antenna. The difference between SAR and real beam radar is that the aperture samples that comprise the SAR are collected at different times by a moving platform. There are several design constraints on a SAR system, including: • Thespeed of the platform and pulserepetition rate (PRF) oftheradarmust be mutually selected so that thesample points of the synthetic array are separated by less than λ/2 to avoid gratinglobes. • ThePRF must be selected so that the swath width is unambiguously sampled. • Apointonthegroundmustbevisibletotheradarrealbeamacrosstheentirelengthofthe synthetic array. This limitsthe sizeof thereal beamantenna. This constraint leadsto the observation that with SAR, the smaller the real-beam antenna, the better the resolution, whereas with SLAR the larger the real-beam antenna, the better the resolution. • TheSARassumes that a ground target has an isotropic signalacross the collection angle of the radar platform as it flies along the synthetic array. TheresolutionoftheunfocusedSARislimitedbecausetheslantrangetoascattereratafixedlocation on the surface changes along the synthetic aperture. If we limit the synthetic aperture to a length so that the range from every array point in the aperture to a fixed surface location differs by less than λ/8, then the cross-rangeresolution of the unfocused SAR is limited to: δ cr =  Rλ/2 33.2.3 Focused Synthetic Aperture Radar The cross-range limitation of an unfocused SAR can be removed by focusing the data, as in optics. The focusing procedure for the SAR involves adjusting the phase of the received signal for every range sample in the image so that all of the points processed in cross-range through the synthetic beamformer appear to be at the same range. The phase error at each range sample used to form the SAR image is φ = 2π λ  d 2 n R  radiar where d n is the cross-range distance from the beam center, R is the slant range to the point on the ground from the beam center, and λ is the wavelength. The range samples can be focused before cross-rangeprocessingbyremovingthisphaseerrorfromthephasehistorydata. Notethat each data point hasa different phasecorrection basedon thealong-t rack positionof thesensor and thepoint’s range from the sensor. When focusingis performed, theresulting SARimage resolution isindependent ofthe slantrange between the sensor and ground. This can be shown as follows: δ cr = Rθ s c  1999 by CRC Press LLC where, θ s ≈ λ 2L e and L e ≈ Rλ L a therefore, δ cr ≈ L a /2 The effective beamwidthof thesynthetic apertureis approximately λ/2L e wherethe factoroftwo comes from the two-way propagation of the energy (the exact effective beamwidth depends on the synthetic array taper used to control sidelobes). The length of the effective aperture (L e ) is limited by the fact that a given scatterer on the surface must be in the mainbeam of the real radar beam for every position along the synthetic aperture. The result is that the resolution of the SAR when the data is focused is approximately L a /2. SAR processing can also be developed by considering the Doppler of the radar signal from the surface as first done by Wiley in 1951. When the real beamwidth of the SAR is small, a point on the surface has an approximately linearly decreasing Doppler frequency as it passes through the main beam of the real SAR beamwidth. This time varying Doppler frequency has been shown to be approximately: f d (t) = 2ν 2 |t −t 0 | λR where ν is the velocity of the platform and t 0 is the time that the point scatterer is in the center of the main beam. The change in Doppler frequency as the point passes through the main beam is 2ν 2 T d /λR,andT d isthetimethatthepointisinthemainbeam. AswithlinearFMpulsecompression, covered in Section 33.2.1, this Doppler signal can be processed through a filter to produce a higher cross-rangeresolutionsignalwhich islimitedbythe size of therealaperturejustaswith thesynthetic antenna interpretation (δ cr = L a /2). In a modern SAR system, typically both pulse compression (syntheticrangeprocessing)andasyntheticaperture(syntheticcross-rangeprocessing)areemployed. In most cases, these transformations are separable where the range processing is referred to as “fast time” processing and the cross-range processing is referred to as “slow-time” processing. A modern SAR system requires several additional signal processing algorithms to achieve high resolution imagery. In practice, the platform does not fly a straight and level path, so the phase of the raw receive signal must be adjusted to account for aircraft perturbations, a procedure called motion compensation. In addition, since it is difficult to exactly estimate the platform parameters necessarytofocustheSARimage,anautofocusalgorithmisused. Thisalgorithmderivestheplatform parameters from the raw SAR data to focus the imagery. There is also an interpolation algorithm that converts from polar to rectangular formats for the imagerydisplay. Most modern SAR systems form imagery digitallyusing either an FFTor a bankof matched filters. Typically, aSAR will operate in either a stripmap or spotlight mode. In the stripmap mode, the SAR antenna is t ypically pointed perpendicular to the flight path (althoughit may be squinted slightly to one side). A stripmap SAR keeps its antenna position fixe d and collects SAR imageryalong a swath to one side of the platform. A spotlight SAR can move its antenna to point at a position on the ground for a longer period of time(thusactuallyachievingcross-rangeresolutionsevengreaterthantheaperturelengthover two). Many SAR systems support both stripmap and spotlight modes, using the stripmap mode to cover large areas of the surface in a slightly lower resolution mode, and spotlight modes to p erform very high resolution imaging of areas of high interest. 33.3 SAR Image Enhancement In thissection we review a few techniques forremoving speckle noisefrom SAR imagery. Removing the speckle can make it easier to extract information from SAR imagery and improves the visual quality. c  1999 by CRC Press LLC [...]... Transactions on Antennas and Propagation, IEEE Transactions on Signal Processing, and IEEE Transactions on Image Processing Conferences IEEE National Radar Conference, IEEE International Radar Conference, and the International Society for Optical Engineering (SPIE) has several SAR Conferences There are numerous open areas of research on SAR signal processing algorithms including: • Still developing an understanding... Radar: Systems and Signal Processing, John Wiley & Sons, New York, 1991 [2] Wehner, D.R., High Resolution Radar, 2nd ed., Artech House, Boston, MA, 1995 [3] Stimson, G.W., Introduction to Airborne Radar, Hughes Aircraft Company, 1983 [4] Skolnik, M., Introduction to Radar Systems, 2nd ed., McGraw-Hill, New York, 1980 [5] Novak, L., Burl, M., and Irving, B., Optimal polarimetric processing for enhanced... speckle reduction operation on target signals It only minimizes the clutter There has been recent work on polarimetric speckle reduction filters that both reduce the clutter speckle while preserving the target signal Fig 33.4 shows the three polarimetric channels and the resulting PWF image for an ADTS SAR chip of a target-like object FIGURE 33.4: Polarimetric processing of SAR data to reduce speckle... and empirically modeling the clutter When the combination of the radar system design and clutter properties results in images that contain large amounts of speckle, it is desirable to perform additional processing to reduce the speckle One approach for speckle reduction is to noncoherently spatially average adjacent resolution cells, sacrificing resolution for the speckle reduction This spatial averaging... number of false alarms (hundreds per square kilometer in single polarimetric channel, one foot resolution imagery) [5] In order to further reduce the false alarm rate and classify the targets, further processing is necessary on the output of the pre-detector One widely used approach for performing this classification operation is to apply a linear filter bank classifier to the ROIs identified by the pre-detector . “fast time” processing and the cross-range processing is referred to as “slow-time” processing. A modern SAR system requires several additional signal processing. thatDoppler shift the frequency of the receive signal introduces ambiguities resulting in additional signal processing issues thatmust be addressed. Thereis