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2011-06-10
Linear Array SAR Imaging via Compressed Sensing
By
Progress In Electromagnetics Research, Vol. 117, 299-319, 2011
Abstract
In recent years, various attempts have been undertaken to obtain three-dimensional (3-D) reflectivity of observed scene from synthetic aperture radar (SAR) technique. Linear array SAR (LASAR) has been demonstrated as a promising technique to achieve 3-D imaging of earth surface. The common methods used for LASAR imaging are usually based on matched filter (MF) which obeys the traditional Nyquist sampling theory. However, due to limitation in the length of linear array and the ``Rayleigh'' resolution, the standard MF-based methods suffer from low resolution and high sidelobes. Hence, high resolution imaging algorithms are desired. In LASAR images, dominating scatterers are always sparse compared with the total 3-D illuminated space cells. Combined with this prior knowledge of sparsity property, this paper presents a novel algorithm for LASAR imaging via compressed sensing (CS). The theory of CS indicates that sparse signal can be exactly reconstructed in high Signal-Noise-Ratio (SNR) level by solving a convex optimization problem with a very small number of samples. To overcome strong noise and clutter interference in LASAR raw echo, the new method firstly achieves range focussing by a pulse compression technique, which can greatly improve SNR level of signal in both azimuth and cross-track directions. Then, the resolution enhancement images of sparse targets are reconstructed by L1 norm regularization. High resolution properties and point localization accuracies are tested and verified by simulation and real experimental data. The results show that the CS method outperforms the conventional MF-based methods, even if very small random selected samples are used.
Citation
Shun-Jun Wei, Xiao-Ling Zhang, and Jun Shi, "Linear Array SAR Imaging via Compressed Sensing," Progress In Electromagnetics Research, Vol. 117, 299-319, 2011.
doi:10.2528/PIER11033105
References

1. Park, J.-I. and K.-T. Kim, "A comparative study on isar imaging algorithms for radar target identification," Progress In Electromagnetics Research, Vol. 108, 155-175, 2010.
doi:10.2528/PIER10071901

2. Lazaro, A., D. Girbau, and R. Villarino, "Simulated and experimental investigation of microwave imaging using UWB," Progress In Electromagnetics Research, Vol. 94, 263-280, 2009.
doi:10.2528/PIER09061004

3. Guo, D., H. Xu, and J. Li, "Extended wavenumber domain algorithm for highly squinted sliding spotlight SAR data processing," Progress In Electromagnetics Research, Vol. 114, 17-32, 2011.

4. Zhang, M., Y. W. Zhao, H. Chen, and W.-Q. Jiang, "SAR imaging simulation for composite model of ship on dynamic ocean scene," Progress In Electromagnetics Research, Vol. 113, 395-412, 2011.
doi:10.2528/PIER11071501

5. Burgmann, R., P. A. Rosen, and E. J. Fielding, "Synthetic aperture radar interferometry to measure Earth's surface topography and its deformation ," Annual Review of Earth and Planetary Sciences, Vol. 28, 169-209, 2000.
doi:10.1146/annurev.earth.28.1.169

6. Li, C. and D.-Y. Zhu, "A residue-pairing algorithm for insar phase unwrapping," Progress In Electromagnetics Research, Vol. 95, 341-354, 2009.
doi:10.2528/PIER09070706

7. Wu, B.-I., M. C. Yeung, Y. Hara, and J. A. Kong, "Insar height inversion by using 3-D phase projection with multiple baselines," Progress In Electromagnetics Research, Vol. 91, 173-193, 2009.
doi:10.2528/PIER09020902

8. Reigber, A. and A. Moreira, "First demonstration of airborne SAR tomography using multibaseline L-band data," IEEE Transactions on Geoscience and Remote Sensing, Vol. 38, No. 5, 2142-2152, 2000.
doi:10.1109/36.868873

9. Solimene, R., A. Brancaccio, R. Di Napoli, and R. Pierri, "3D sliced tomographic inverse scattering experimental results," Progress In Electromagnetics Research, Vol. 105, 1-13, 2010.
doi:10.2528/PIER10050705

10. Teng, H. T., H.-T. Ewe, and S. L. Tan, "Multifractal dimension and its geometrical terrain properties for classification of multi-band multi-polarized SAR image," Progress In Electromagnetics Research, Vol. 104, 221-237, 2010.
doi:10.2528/PIER10022001

11. Klare, J., A. Brenner, and J. Ender, "A new airborne radar for 3D imaging-image formation using the ARTINO principle," 6th European Conference on Synthetic Aperture Radar 2006, 2006.

12. WeiB, M., O. Peters, and J. Ender, "First Flight trials with ARTINO," 7th European Conference on Synthetic Aperture Radar, Vol. 4, 187-190, 2008.

13. Du, L., Y.-P. Wang, W. Hong, et al. "A three-dimensional range migration algorithm for downward-looking 3D-SAR with single-transmitting and multiple receiving linear array antennas," EURASIP Journal on Advances in Signal Processing, Vol. 2010, 1-15, 2010.
doi:10.1155/2010/957916

14. Zhang, D.-H. and X.-L. Zhang, "Downward-looking 3-D linear array SAR imaging based on chirp scaling algorithm," 2nd Asian-Paci¯c Conference on Synthetic Aperture Radar (APSAR 2009), 1043-1046, 2009.

15. Shi, J., X.-L. Zhang, J.-Y. Yang, et al. "APC trajectory design for `One-Active' linear-array three-dimensional imaging SAR," IEEE Transactions on Geoscience and Remote Sensing, Vol. 48, No. 3, 1470-1486, 2010.
doi:10.1109/TGRS.2009.2031430

16. Soumekh, M., Synthetic Aperture Radar Signal Processing with Matlab Algorithms, Wiley, New York, 1999.

17. Jin, Y.-Q., "Polarimetric scattering modeling and information retrieval of SAR remote sensing | A review of FDU work," Progress In Electromagnetics Research, Vol. 104, 333-384, 2010.
doi:10.2528/PIER10020101

18. Donoho, D., "Compressed sensing," IEEE Trans. Inf. Theory, Vol. 52, No. 4, 1289-1306, April 2006.
doi:10.1109/TIT.2006.871582

19. Candes, E. J. and M. Wakin, "An introduction to compressive sampling," IEEE Signal Processing Magazine, 21-30, March 2008.
doi:10.1109/MSP.2007.914731

20. Patel, V. M., G. R. Easley, and D. M. Healy, "An introduction to compressive sampling," IEEE Signal Processing Magazine, 21-30, March 2008.

21. Herman, M. A. and T. Strohmer, "High-resolution radar via compressed sensing," IEEE Trans. on Signal Processing, Vol. 57, No. 6, 2275-2284, June 2009.
doi:10.1109/TSP.2009.2014277

22. Zhang, L., M.-D. Xing, C.-W. Qiu, et al. "Achieving higher resolution ISAR imaging with limited pulses via compressed sampling," IEEE Transactions on Geoscience and Remote Sensing, Vol. 4, No. 2, 567-571, 2009.

23. Liu, Y.-B., Y.-H. Quan, J. Li, et al. "SAR imaging of multiple ships based on compressed sensing," 2nd Asian-Pacific Conference on Synthetic Aperture Radar (APSAR 2009), 112-115, 2009.
doi:10.1109/APSAR.2009.5374294

24. Potter, L. C., E. Ertin, J. T. Parker, and M. Çetin, "Sparsity and compressed sensing in radar imaging," Proceedings of the IEEE, Vol. 98, No. 6, 1006-1020, 2010.
doi:10.1109/JPROC.2009.2037526

25. Wei, S.-J., X.-L. Zhang, J. Shi, and G. Xiang, "Sparse reconstruction for SAR imaging based on compressed sensing," Progress In Electromagnetics Research, Vol. 109, 63-81, 2010.
doi:10.2528/PIER10080805

26. Zhu, X.-X. and R. Bamler, "Tomographic SAR inversion by L1-norm regularization | The compressive sensing approach," IEEE Transactions on Geoscience and Remote Sensing, Vol. 48, No. 10, 3839-3846, 2010.
doi:10.1109/TGRS.2010.2048117

27. Budillon, A., A. Evangelista, and G. Schirinzi, "Three-dimensional SAR focussing from multipass signals using compres-sive sampling," IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 1, 488-499, 2010.
doi:10.1109/TGRS.2010.2054099

28. Chan, Y. K. and V. C. Koo, "An introduction to Synthetic Aperture Radar (SAR)," Progress In Electromagnetics Research B, Vol. 2, 27-60, 2008.
doi:10.2528/PIERB07110101

29. Chua, M. Y. and V. C. Koo, "FPGA-based chirp generator for high resolution UAV SAR," Progress In Electromagnetics Research, Vol. 99, 71-88, 2009.
doi:10.2528/PIER09100301

30. Lim, S.-H., J.-H. Han, S.-Y. Kim, and N.-H. Myung, "Azimuth beam pattern synthesis for airborne SAR system optimization," Progress In Electromagnetics Research, Vol. 106, 295-309, 2010.
doi:10.2528/PIER10061901

31. Sun, J., S. Mao, G. Wang, and W. Hong, "Polar format algorithm for spotlight bistatic SAR with arbitrary geometry configuration," Progress In Electromagnetics Research, Vol. 103, 323-338, 2010.
doi:10.2528/PIER10030703

32. Chan, Y. K. and S. Y. Lim, "Synthetic Aperture Radar (SAR) signal generation," Progress In Electromagnetics Research B, Vol. 1, 269-290, 2008.
doi:10.2528/PIERB07102301

33. Nie, X., D.-Y. Zhu, and Z.-D. Zhu, "Application of synthetic bandwidth approach in SAR polar format algorithm using the deramp technique," Progress In Electromagnetics Research, Vol. 80, 447-460, 2008.
doi:10.2528/PIER07121409

34. Sabry, R. and P. W. Vachon, "Advanced polarimetric synthetic aperture radar (SAR) and electro-optical (EO) data fusion through uni¯ed coherent formulation of the scattered EM field," Progress In Electromagnetics Research, Vol. 84, 189-203, 2008.
doi:10.2528/PIER08071005

35. Crowgey, B. R., E. J. Rothwell, L. C. Kempel, and E. L. Mokole, "Comparison of UWB short-pulse and stepped-frequency radar systems for imaging through barriers,", Vol. 110, 403-419, 2010.
doi:10.2528/PIER10091306

36. Sun, J., S. Mao, G. Wang, and W. Hong, "Polar format algorithm for spotlight bistatic SAR with arbitrary geometry configuration," Progress In Electromagnetics Research, Vol. 103, 323-338, 2010.
doi:10.2528/PIER10030703

37. Chen, S., D. Donoho, and M. A. Saunders, "Atomic decomposition by basis pursuit," SIAM J. Sci. Comput., Vol. 20, No. 1, 33-61, 1999.
doi:10.1137/S1064827596304010

38. Tropp, J. A., "Greed is good: Algrorithm results for sparse approximation," IEEE Trans. Inf. Theory, Vol. 50, No. 10, 2231-2242, October 2004.
doi:10.1109/TIT.2004.834793

39. Needell, D. and R. Vershynin, "Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit," Found Comput. Math., Vol. 9, No. 3, 317-334, June 2009.
doi:10.1007/s10208-008-9031-3

40. Candes, E. J., J. K. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inf. Theory, Vol. 52, No. 2, 489-509, February 2006.
doi:10.1109/TIT.2005.862083

41. Candes, E. J., J. K. Romberg, and T. Tao, "Stable signal recovery from incomplete and inaccurate measurements," Communications on Pure and Applied Mathematics, Vol. 59, No. 8, 1207-1223, 2006.
doi:10.1002/cpa.20124

42. Shi, J., X.-L. Zhang, J.-Y. Yang, et al. "Experiment results on `one-active' LASAR," IEEE Radar Conference, 1-4, 2009.