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Bistatic SAR imaging using Non-Linear Chirp Scaling

Bistatic SAR imaging using Non-Linear Chirp Scaling. By Y. L. Neo Supervisor : Prof. Ian Cumming Industrial Collaborator : Dr. Frank Wong. Agenda. Bistatic SAR Bistatic Image Reconstruction Issues Existing Algorithms Non-Linear Chirp Scaling Algorithm Extension to NLCS Simulation Results

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Bistatic SAR imaging using Non-Linear Chirp Scaling

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  1. Bistatic SAR imaging using Non-Linear Chirp Scaling By Y. L. Neo Supervisor : Prof. Ian Cumming Industrial Collaborator : Dr. Frank Wong Bistatic SAR Imaging using Non-Linear Chirp Scaling

  2. Agenda • Bistatic SAR • Bistatic Image Reconstruction Issues • Existing Algorithms • Non-Linear Chirp Scaling Algorithm • Extension to NLCS • Simulation Results • Conclusions Bistatic SAR Imaging using Non-Linear Chirp Scaling

  3. Bistatic SAR • In a Bistatic configuration, the Transmitter and Receiver are spatially separated and can move along different paths. • Bistatic SAR is important as it provides many advantages • Cost savings by sharing active components • Improved observation geometries • Passive surveillance and improved survivability Bistatic SAR Imaging using Non-Linear Chirp Scaling

  4. Current Research • Several European radar research institutes - DLR, ONERA, QinetiQ and FGAN have embarked on bistatic airborne experiments. Majority of the experiments uses two existing monostatic sensors to synthesize bistatic images. • Satellite missions are also proposed TanDEM – X : proposal for TerraSAR-X single pass interferometry for accurate DEM DTED-3. Interferometric Cartwheel. Excellent paper – Multistatic SAR Satellite Formations: Gerhard Krieger. • Other research involves the use of Bistatic Parasitic SAR. Where a ground based receiver pairs up with a non-cooperative satellite transmitter. Bistatic SAR Imaging using Non-Linear Chirp Scaling

  5. Agenda • Bistatic SAR • Bistatic Image Reconstruction Issues • Existing Algorithms • Non-Linear Chirp Scaling Algorithm • Extension to NLCS • Simulation Results • Conclusions Bistatic SAR Imaging using Non-Linear Chirp Scaling

  6. Image Reconstruction Issues • Bistatic SAR data, unlike monostatic SAR data, is inherently azimuth-variant. • Difficult to derive the spectrum of bistatic signal due to the double square roots term. • Traditional monostatic SAR algorithms based on frequency domain methods are not able to focus bistatic SAR imagery, since targets having the same range of closest approach do not necessarily collapse into the same trajectory in the azimuth frequency domain. Bistatic SAR Imaging using Non-Linear Chirp Scaling

  7. Image Reconstruction Issues • Bistatic SAR has many configurations • parallel tracks, • non-parallel tracks, • stationary receiver etc. • These different configurations make the derivation of the spectrum difficult • Analytical solution is not available, however approximate solution exist – Loffeld’s bistatic equation • Restricted the scope of research to focusing parallel and slightly non-parallel cases Bistatic SAR Imaging using Non-Linear Chirp Scaling

  8. Imaging geometry of bistatic SAR Bistatic SAR Imaging using Non-Linear Chirp Scaling

  9. Agenda • Bistatic SAR • Bistatic Image Reconstruction Issues • Existing Algorithms • Non-Linear Chirp Scaling Algorithm • Extension to NLCS • Simulation Results • Conclusions Bistatic SAR Imaging using Non-Linear Chirp Scaling

  10. Existing Algorithms • Time Domain Correlation • Back Projection Algorithm • K Algorithm • Loffeld’s Bistatic Equations • RDA • Rocca’s Smile Bistatic SAR Imaging using Non-Linear Chirp Scaling

  11. Agenda • Bistatic SAR • Bistatic Image Reconstruction Issues • Existing Algorithms • Non-Linear Chirp Scaling Algorithm • Extension to NLCS • Simulation Results • Conclusions Bistatic SAR Imaging using Non-Linear Chirp Scaling

  12. Non-Linear Chirp Scaling • Existing Non-Linear Chirp Scaling • Based on paper by F. H. Wong, and T. S. Yeo, “New Applications of Nonlinear Chirp Scaling in SAR Data Processing," in IEEE Trans. Geosci. Remote Sensing, May 2001. • Assumes negligible QRCM (for SAR with short wavelength) • shown to work on Monostatic case and the Bistatic case where receiver is stationary • Limitations of this method is unknown • May be extended to other geometries – parallel tracks, non-parallel tracks Bistatic SAR Imaging using Non-Linear Chirp Scaling

  13. Advantages • NLCS can be used to focused bistatic data by finding the perturbation function for each bistatic configuration • NLCS requires no interpolation • NLCS can be used in non-parallel cases • The Linear RCMC step in NLCS eliminates most of the RCM and the range/azimuth phase coupling. • Computational load is comparable to traditional monostatic algorithms. Bistatic SAR Imaging using Non-Linear Chirp Scaling

  14. Main Processing Steps of NLCS Algorithm Range Compression Linear RCMC Baseband Signal Azimuth Compression Non-Linear Chirp Scaling Focused Image Bistatic SAR Imaging using Non-Linear Chirp Scaling

  15. After Range Compression and LRCMC, Point A and Point C now lie in the same range gate. Although they have different chirp rates A C • The trajectories of three point targets in a squinted monostatic case is shown • Point A and Point B has the same Closest range of approach and the same chirp rate. B Monostatic Case Range time Az time Bistatic SAR Imaging using Non-Linear Chirp Scaling

  16. Chirp Rate Equalization (monostatic) Bistatic SAR Imaging using Non-Linear Chirp Scaling

  17. After LRCMC, trajectories at the same range gate do not have the same chirp rates, an equalizing step is necessary • Chirp rates are equalized by phase multiply with a perturbation function hpert(η) along azimuth time . • Monostatic Case • Bistatic Case with Stationary Receiver • Once the Azimuth Chirp Rate is equalized, the image can be focused by an azimuth matched filter. Bistatic SAR Imaging using Non-Linear Chirp Scaling

  18. Agenda • Bistatic SAR • Bistatic Image Reconstruction Issues • Existing Algorithms • Non-Linear Chirp Scaling Algorithm • Extension to NLCS • Simulation Results • Conclusions Bistatic SAR Imaging using Non-Linear Chirp Scaling

  19. Research work done • Added residual QRCMC • Extended the processing to parallel tracks and non-parallel tracks • Azimuth Frequency Matched filter • Secondary Range Compression • Current work • Invariance Region Analysis • Registration to ground plane Bistatic SAR Imaging using Non-Linear Chirp Scaling

  20. Range Compression LRCMC / Linear Phase Correction Baseband Signal Non-Linear Chirp Scaling Residual QRCMC Azimuth Compression Focused Image • We have added a QRCMC to improve the impulse response • Residual QRCM Correction can be performed in the range Doppler domain after the Chirp Rate has been equalized Bistatic SAR Imaging using Non-Linear Chirp Scaling

  21. Residual QRCMC • Uncorrected QRCM will lead to Broadening in Range and Azimuth • The Cubic RCM is very small compared to Quadratic RCM , can be ignored in most cases Without residual QRCMC With residual QRCMC Resolution and PSLR Improves Bistatic SAR Imaging using Non-Linear Chirp Scaling

  22. Perturbation Function • We have extended the NLCS algorithm to Non-Parallel Tracks with the Same Velocity • Using the method similar to the monostatic case and correction of the phase term up to the cubic term, the perturbation function is found to be a cubic function of azimuth time and the coefficient is found to be • Limited to short and medium wavelength system Bistatic SAR Imaging using Non-Linear Chirp Scaling

  23. Azimuth Frequency Matched Filter • Initially used time domain matched filter – correlation (inefficient) • Frequency matched filter is derived using the reversion of power series • Linear phase term has to be removed before applying the reversion of power series Bistatic SAR Imaging using Non-Linear Chirp Scaling

  24. Azimuth Matched Filter • Freq matched filter can be obtained by doing a FT of the equalized Az signal • A relation between azimuth time and azimuth frequency can be obtained by using the Principle of Stationary Phase Bistatic SAR Imaging using Non-Linear Chirp Scaling

  25. Azimuth Matched Filter • The Frequency matched filter is the conjugate of FT signal • Expansion up to third order phase is necessary • - e.g. C band 55deg squint 2m resolution Bistatic SAR Imaging using Non-Linear Chirp Scaling

  26. Limitations • Restriction on patch size, residual RCM difference < 1 range resolution cell – restrict the range extent • The Non-linear chirp scaling uses some approximations – leading to restriction in azimuth extent • Range Doppler Coupling for large QRCM – Secondary Range Compression is necessary • Algorithm suitable for shorter wavelengths (S, C , X, K band ) and cases where QRCM is not too significant Bistatic SAR Imaging using Non-Linear Chirp Scaling

  27. Invariance Region Analysis • The range invariance region to keep range and azimuth resolution degradation less than 10% for a 10 km by 10km patch. • Bistatic case, imaging at broadside with Tx slant range of 40km, lateral separation of 20km and a bistatic angle of 9 deg. • Bistatic case, Tx imaging at 30 deg squint, Tx slant range of 40km, lateral separation of 20km and squint of 30 deg. Bistatic SAR Imaging using Non-Linear Chirp Scaling

  28. Secondary Range Compression • Range Doppler Coupling occurs for large QRCM i.e. longer wavelength and higher resolution cases • Secondary Range Compression must be performed before Quadratic Range Cell Migration for these cases • Additional processing required will reduce the efficiency of the algorithm • Still investigating this part. Preliminary results shows that quadratic range migration of 6 range resolution cells does not produce significant range Doppler coupling Diagram referenced from “the BOOK” – Digital Processing of Synthetic Aperture Radar Data Bistatic SAR Imaging using Non-Linear Chirp Scaling

  29. Illustration of SRC Bistatic SAR Imaging using Non-Linear Chirp Scaling

  30. Agenda • Bistatic SAR • Bistatic Image Reconstruction Issues • Existing Algorithms • Non-Linear Chirp Scaling Algorithm • Extension to NLCS • Simulation Results • Conclusions Bistatic SAR Imaging using Non-Linear Chirp Scaling

  31. Non-parallel flight, dissimilar velocity Transmitter squinted at 40 degreesand both platforms moving in a non-parallel configuration with lateral separation of 3km and with Vt = 200m/s and Vr =220m/s1 parallel to Transmitter . It is a C-band system with wavelength = 0.06m, 3dB beamwidth = 1.9degree, PRF = 185Hz. Range bandwidth of 75MHz and Azimuth bandwidth about 160Hz. The imaged area has 25 point targets Bistatic SAR Imaging using Non-Linear Chirp Scaling

  32. Before Registration to Ground Plane Bistatic SAR Imaging using Non-Linear Chirp Scaling

  33. After Registration to Ground Plane Bistatic SAR Imaging using Non-Linear Chirp Scaling

  34. Impulse response Bistatic SAR Imaging using Non-Linear Chirp Scaling

  35. Agenda • Bistatic SAR • Bistatic Image Reconstruction Issues • Existing Algorithms • Non-Linear Chirp Scaling Algorithm • Extension to NLCS • Simulation Results • Conclusions Bistatic SAR Imaging using Non-Linear Chirp Scaling

  36. Conclusions • Illustrated the use of NLCS to focus bistatic SAR • Show the extensions to the NLCS to improve its processing capabilities • Simulated a non-parallel track example and the results Bistatic SAR Imaging using Non-Linear Chirp Scaling

  37. Future work • Invariance Region Analysis. • Secondary Range Compression. • Registration. • Comparison with existing algorithms. • How the existing algorithms relate to one another. Bistatic SAR Imaging using Non-Linear Chirp Scaling

  38. Questions? Bistatic SAR Imaging using Non-Linear Chirp Scaling

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