1. Perspectives on SAR Processing Ian Cumming Professor Emeritus Radar Remote Sensing Group Dept. of Electrical and Computer Engineering University of British Columbia

2. Perspectives on SAR Processing 1.Some SAR processing history 2.Review of current SAR proc. algorithms 3.Which algorithms are used today? 4.Some image examples 5.Summary and final thoughts Sept. 11, 2007 2 Cumming – ASAR 2007

3. Some Processing History In 1976, SAR data were processed by coherent optics In 1976, SAR data were processed by coherent optics only one book available only one book available very hard to understand for a DSP engineer very hard to understand for a DSP engineer used laser beams and lenses to focus image used laser beams and lenses to focus image fast, but limited dynamic range fast, but limited dynamic range must be a better way – digital processing! must be a better way – digital processing! Challenge of digital processing Challenge of digital processing modest computing resources (memory & speed) modest computing resources (memory & speed) processing algorithms not known processing algorithms not known received signal model was needed (geometry) received signal model was needed (geometry) limited satellite orbit knowledge limited satellite orbit knowledge Sept. 11, 2007 3 Cumming – ASAR 2007

4. Early Airborne Processing In 1970’s, CCRS obtained an airborne SAR from ERIM In 1970’s, CCRS obtained an airborne SAR from ERIM Installed on a Convair-580 Installed on a Convair-580 Previous processor was optical Previous processor was optical MDA contracted to built an on-board real-time processor MDA contracted to built an on-board real-time processor First RTP delivered in 1979 (additional units in 1985) First RTP delivered in 1979 (additional units in 1985) Sept. 11, 2007 4 Cumming – ASAR 2007

5. Early Airborne Processing Processor characteristics Processor characteristics time-domain correlation time-domain correlation X-band, no RCMC needed X-band, no RCMC needed built from discrete components built from discrete components multiplier-accumulator chips, small memory chips 4 giga ops per second in one chassis performed azimuth compression first, then range compression performed azimuth compression first, then range compression real-time waterfall display on-board real-time waterfall display on-board Sept. 11, 2007 5 Cumming – ASAR 2007 On-board real-time processor on CCRS Convair-580

6. Early Satellite Processing SEASAT (October 1978) SEASAT (October 1978) developed detailed model of satellite motion developed detailed model of satellite motion led to received signal model led to received signal model matched filtering done by FD correlation process matched filtering done by FD correlation process had to separate range and azimuth processing had to separate range and azimuth processing to fit in to computer resources range cell migration correction a challenge range cell migration correction a challenge needed interpolator to eliminate paired echos Sept. 11, 2007 6 Cumming – ASAR 2007

7. First Digital SEASAT Image Sept. 11, 2007 7 Cumming – ASAR 2007 Featured in Aviation Week, Feb. 26, 1979

8. Typical product 1979-1981 Sept. 11, 2007 8 Cumming – ASAR 2007 Niagara Falls 40 x 40 km scene 25 m resolution 4 looks 40 hours to process “big” minicomputer corner turning on disc needed autofocus for L-band

9. Review of SAR Processing Algorithms Developed primarily for satellite SAR processing Developed primarily for satellite SAR processing Range/Doppler (1978)JPL & MDA Range/Doppler (1978)JPL & MDA Time-domain (1978) Time-domain (1978) SPECAN (1980)MDA SPECAN (1980)MDA Omega-K (1988)Polimi, Italy Omega-K (1988)Polimi, Italy Chirp scaling (1992)CCRS, DLR, MDA Chirp scaling (1992)CCRS, DLR, MDA Sept. 11, 2007 9 Cumming – ASAR 2007

10. SAR Signal Model Sept. 11, 2007 10 Cumming – ASAR 2007 Range and azimuth extent of signal received from a point target (shown in red) The signal in the two axes is not orthogonal because of the curvature – if it were, the processing would be quite simple The processing is achieved by a matched filtering (correlation) operation, but what to do about the curvature, if we are restricted to 1-D operations?

11. Range/Doppler Algorithm – 1 Developed at MDA and JPL Developed at MDA and JPL 1977-79 plus later refinements 1977-79 plus later refinements Used 1-D frequency domain correlation Used 1-D frequency domain correlation processing separated in range and azimuth dimensions processing separated in range and azimuth dimensions for computing efficiency & memory limitations for computing efficiency & memory limitations Had to deal with range migration MDA recognized importance of accurate interpolation MDA recognized importance of accurate interpolation JPL developed secondary range compression to deal with range-azimuth coupling when migration large – 1984 JPL developed secondary range compression to deal with range-azimuth coupling when migration large – 1984 Sept. 11, 2007 11 Cumming – ASAR 2007

12. Range/Doppler Algorithm – 2 Sept. 11, 2007 12 Cumming – ASAR 2007 So named because the key operations of RCMC and azimuth compression are performed in the range time/azimuth frequency (i.e., Doppler) domain. SRC not shown, as it can be applied in different places

13. Range/Doppler Algorithm – 3 Sept. 11, 2007 13 Cumming – ASAR 2007 A one-dimensional interpolator can correct multiple targets in the range/Doppler domain. After the interpolation, the locus of energy is corrected, but a phase error persists, which can defocus the image. SRC was implemented to correct the phase error.

14. Range/Doppler Algorithm – 4 Sept. 11, 2007 14 Cumming – ASAR 2007 When the squint is high or the aperture wide, SRC is needed to ensure accurate focusing. SRC is mainly a function of azimuth frequency, then range frequency. Therefore, it is best to apply SRC in the 2-D frequency domain. It is applied efficiently by a phase multiply after an azimuth FFT is done.

15. Range/Doppler Algorithm – 5 Sept. 11, 2007 15 Cumming – ASAR 2007 Processing with SRC can be done by modifying the range FM rate in rangcomp. This is the approximate approach.

16. Range/Doppler Algorithm – 6 Sept. 11, 2007 16 Cumming – ASAR 2007 This slide shows how the target focus deteriorates when the squint angle is increased. With no SRC, the focus deteriorates quite fast with squint. Approx SRC allows a fair amount of squint, but the accurate SRC (not shown) allows a large squint.

17. Range/Doppler Algorithm – 7 Sept. 11, 2007 17 Cumming – ASAR 2007 This slide shows the RDA with 1)No SRC 2)Accurate SRC 3)Approximate SRC The Option 3 is very simple to apply, and is most frequently used. Which one is needed depends on the squint angle and the width of the aperture. Option 3 can be applied when needed.

18. 18October 2007Cumming – Perscectives on SAR Processing Range/Doppler Algorithm – 8 Easy to understand & program uses only 1-D operations uses only 1-D operations Accommodates range-variant parameters easily (except SRC) Doppler centroid Doppler centroid azimuth FM rate azimuth FM rate Interpolator introduces a small but controllable error Cannot handle very wide apertures or high squint unless SRC is applied as needed AdvantagesDisadvantages

19. 19October 2007Cumming – Perscectives on SAR Processing City of Vancouver RDA processing RADARSAT-1 FINE mode 8 m resolution

20. 20October 2007Cumming – Perscectives on SAR Processing Convair-580 Data processed using RDA

21. 21October 2007Cumming – Perscectives on SAR Processing Chirp Scaling Algorithm – 1 Want to improve accuracy by replacing the RCMC interpolator with a more accurate DSP operator The chirp scaling concept  if a linear FM signal is shifted in frequency, it will be shifted in time after pulse compression same concept that causes a railway train to be imaged off the tracks  the train’s Doppler shift moves the train in azimuth after azimuth compression same concept that causes a railway train to be imaged off the tracks  the train’s Doppler shift moves the train in azimuth after azimuth compression Chirp scaling is used to perform differential RCMC in the range/Doppler domain, to equalize the curvature over range

22. 22October 2007Cumming – Perscectives on SAR Processing Chirp Scaling Algorithm – 2 Illustrates how a chirp (Panel 1) multiplied by a sine wave (Panel 2) causes a registration shift in the compressed pulse (Panel 4). Because the matched filter (not shown) has a zero centre frequency, the compressed pulse is registered at the zero frequency point of the scaled signal (Panel 3). This shift performs RCMC in the range/Doppler domain, assuming range compression is not done yet (because the amount of shift is limited by the range oversampling, only differential RCMC is done with chirp scaling). The sine wave scaling is applied in the range direction, with a different frequency at each azimuth frequency. Note that the resulting shift is constant with range.

23. 23October 2007Cumming – Perscectives on SAR Processing Chirp Scaling Algorithm – 3 But the shift needs to be varied with range (as well as with azimuth frequency). As the change with range is small, this can be achieved by making the frequency of the scaling function change slowly with range. A linear FM scaling function makes the range shift vary linear with range (called linear chirp scaling). This linear form is adequate for most satellite SAR parameters.

24. 24October 2007Cumming – Perscectives on SAR Processing Chirp Scaling Algorithm – 4 The 2-D freq domain can be used to perform the remaining RCMC without an interpolator. Range compression, SRC also done. SRC is accurate as it is range and az freq dependent. All operations are FFTs and phase multiplies Chirp scaling is applied in the RD domain Subsequent ops are the same as the RDA

25. 25October 2007Cumming – Perscectives on SAR Processing SRTM Image Processed by CSA

26. 26October 2007Cumming – Perscectives on SAR Processing Chirp Scaling Algorithm – 5 More accurate RCMC no interpolator no interpolator The 2-D frequency domain is available to apply a more accurate form of SRC better phase accuracy better phase accuracy Can handle slightly wider apertures and squint angles Requires 2-D processing Additional complexity if the Doppler centroid changes quickly with range Assumes SRC is independent of range Inefficient if range compression already done AdvantagesDisadvantages For many satellite SAR parameters, the advantages over the RDA tend to outweigh the disadvantages, but RDA preferred for zero Doppler cases.

27. 27October 2007Cumming – Perscectives on SAR Processing Omega-K Algorithm – 1 If the range equation is hyperbolic (straight line sensor motion), and the effective radar velocity is independent of range, an “exact” solution can be obtained this assumption is excellent for airborne radars (after mocomp) and quite good for satellite SARs this assumption is excellent for airborne radars (after mocomp) and quite good for satellite SARs Engineers at the Polytechnic of Milano discovered this, adapting an algorithm known as Stolt interpolation from the seismic field All processing is done in the 2-D frequency domain

28. Omega-K Algorithm – 2 Sept. 11, 2007 28 Cumming – ASAR 2007 The Stolt interpolation consists of scaling and shifting operations, as illustrated by a point target simulation. Col 1: phase plot in 2-D FD Col 2: range slices in 2-D FD Col 3: data after range IFFT (2-D energy & 1-D azimuth slice) The simulation starts with data after the bulk compression, and shows the effects of the scaling and shifting separately. SRC is done exactly during the bulk compression – the Stolt interpolation effectively makes the signal stationary in range and azimuth.

29. 29October 2007Cumming – Perscectives on SAR Processing Omega-K Algorithm – 3 SIVAM X-band airborne radar built by MDA Spotlight operation – 1.8 m resolution

30. 30October 2007Cumming – Perscectives on SAR Processing Omega-K Algorithm – 4 Most accurate algorithm if constant-velocity assumption valid (SRC exact) Accuracy not affected by wide aperture and high squint Fairly easy to program if Doppler centroid does not vary much with range An interpolation is needed in the 2-D FD Cannot handle large changes of Doppler frequency with range efficiently need range block processing AdvantagesDisadvantages

31. 31October 2007Cumming – Perscectives on SAR Processing SPECAN Algorithm When the signal is a chirp, it can be deramped using a phase multiply, making it a sine wave a single FFT then focuses the data a single FFT then focuses the data Single-look version was developed many years ago multilook version developed in 1979 under an ESTEC contract for on-board processing multilook version developed in 1979 under an ESTEC contract for on-board processing Has the most efficient computing, but the worst image quality, notably phase properties particularly suited to burst-mode data, such as ScanSAR particularly suited to burst-mode data, such as ScanSAR

32. 32October 2007Cumming – Perscectives on SAR Processing RADARSAT-1 ScanSAR Narrow 300 km wide SPECAN processing Vancouver Island

33. 33October 2007Cumming – Perscectives on SAR Processing Doppler Centroid Estimation Considered a mature technology yet processing mistakes are still made yet processing mistakes are still made Recommend a new approach take a global view take a global view use spatial diversity over a wide area use spatial diversity over a wide area use quality checks and filtering to eliminate bad regions use quality checks and filtering to eliminate bad regions use a physical geometry model for overall estimate use a physical geometry model for overall estimate use phase increments for primary estimator use phase increments for primary estimator Can be used for specialized applications such as ocean current estimation such as ocean current estimation

34. More details can be found in our “SAR Processing” book Published by Artech House January 2005 Also to be published in Chinese, November 2007 34

35. Summary – 1 RDA RDA a well-known algorithm for general use (30 years experience) a well-known algorithm for general use (30 years experience) except when the aperture is wide and the squint angle is high except when the aperture is wide and the squint angle is high CSA CSA a little more accurate than the RDA, as long as the Doppler parameters do not change too quickly with range a little more accurate than the RDA, as long as the Doppler parameters do not change too quickly with range WKA WKA the most accurate as long as the flight path is linear and the velocity does not change with range (well suited to airborne applications) the most accurate as long as the flight path is linear and the velocity does not change with range (well suited to airborne applications) SPECAN SPECAN needs the least memory and fewest DSP operations needs the least memory and fewest DSP operations ideal for low-resolution imaging ideal for low-resolution imaging Sept. 11, 2007 35 Cumming – ASAR 2007

36. Summary – 2 Many choices of algorithm are available Many choices of algorithm are available Best algorithm for each application depends on Best algorithm for each application depends on geometry and radar parameters geometry and radar parameters accuracy required accuracy required efficiency required efficiency required Most commonly-used algorithm for general precision processing seems to be the RDA, followed by WKA and the CSA Most commonly-used algorithm for general precision processing seems to be the RDA, followed by WKA and the CSA but a systems study needs to examine the pros and cons for each radar situation but a systems study needs to examine the pros and cons for each radar situation SPECAN is commonly used for ScanSAR and quicklook processing SPECAN is commonly used for ScanSAR and quicklook processing Sept. 11, 2007 36 Cumming – ASAR 2007

37. Current & Future Research Many people consider SAR processing for conventional (remote sensing) SARs to be a mature subject, not requiring significant further development Many people consider SAR processing for conventional (remote sensing) SARs to be a mature subject, not requiring significant further development Current work seems to be directed towards advanced items such as: Current work seems to be directed towards advanced items such as: bistatic SAR processing bistatic SAR processing ground moving target detection (GMTI) ground moving target detection (GMTI) information extraction, e.g. information extraction, e.g. classification of polarimetric SAR data classification of polarimetric SAR data change detection through interferometry change detection through interferometry polarimetric interferometry polarimetric interferometry Sept. 11, 2007 37 Cumming – ASAR 2007

38. Final Word Ever since working with ESTEC in 1979, on- board, real-time, digital SAR processing on a satellite has been a dream Ever since working with ESTEC in 1979, on- board, real-time, digital SAR processing on a satellite has been a dream For various technical, financial and strategic reasons, it has not been implemented yet For various technical, financial and strategic reasons, it has not been implemented yet it is becoming feasible now, although its necessity is not justified As a compromise, I would love to build a real- time Doppler estimator As a compromise, I would love to build a real- time Doppler estimator would give the most accurate antenna steering possible, and would give the most accurate antenna steering possible, and be a technical showcase ! be a technical showcase ! Sept. 11, 2007 38 Cumming – ASAR 2007