PIER
 
Progress In Electromagnetics Research
ISSN: 1070-4698, E-ISSN: 1559-8985
Home | Search | Notification | Authors | Submission | PIERS Home | EM Academy
Home > Vol. 127 > pp. 259-275

APPLICATIONS OF COMPRESSED SENSING FOR MULTIPLE TRANSMITTERS MULTIPLE AZIMUTH BEAMS SAR IMAGING

By J. Li, S. Zhang, and J. Chang

Full Article PDF (916 KB)

Abstract:
High speed analog-to-digital (A/D) sampling and a large amount of echo storage are two basic challenges of high resolution synthetic aperture radar (SAR) imaging. In this paper, a novel SAR imaging algorithm which named CS-MTMAB is proposed based on compressed sensing (CS) and multiple transmitters multiple azimuth beams (MTMAB). In particular, this new algorithm, which respectively reconstructs the targets in range and azimuth directions via CS technique, simultaneously provides a high resolution and wideswath two-dimensional map of the spatial distribution of targets with a significant reduction in the number of data samples beyond the Nyquist theorem and with an implication in simplification of radar architecture. The simulation results and analysis show that this new imaging scheme allows the aperture to be compressed and presents many important applications and advantages among which include reduced on-board storage constraints, higher resolution, lower peak side-lobe ratio (PSLR) and integrated side-lobe ratio (ISLR), less sampled data than the traditional SAR imaging algorithm, and also indicate that it has high robustness and strong immunity in the presence of serious noise. Finally, the real raw airborne SAR data experiment is performed to validate the proposed processing procedure.

Citation:
J. Li, S. Zhang, and J. Chang, "Applications of compressed sensing for multiple transmitters multiple azimuth beams SAR imaging," Progress In Electromagnetics Research, Vol. 127, 259-275, 2012.
doi:10.2528/PIER12021307
http://www.jpier.org/pier/pier.php?paper=12021307

References:
1. 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

2. Currie, A. and M. A. Brown, "Wide swath SAR," Proc. Inst. Electr. Eng. F - Radar Signal Process., Vol. 139, No. 2, 122-135, 1992.
doi:10.1049/ip-f-2.1992.0016

3. Currie, A., "Wide-swath SAR imaging with multiple azimuth beams," IEE Colloquium on Synthetic Aperture Radar, Vol. 29, No. 3/1-3/4, London, 1989.

4. Delaurentis, J., "Multipath synthetic aperture radar imaging," IEE Radar, Sonar and Navig., Vol. 5, No. 5, 561-572, 2011.
doi:10.1049/iet-rsn.2010.0225

5. Wu, W., P. Huang, and Y.-K. Deng, "Multi-channel specmb-tops SAR for high-resolution wide-swath imaging," Progress In Electromagnetics Research, Vol. 116, 533-551, 2011.

6. 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

7. Xu, W., P. Huang, and Y.-K. Deng, "MIMO-tops mode for high-resolution ultra-wide-swath full polarimetric imaging," Progress In Electromagnetics Research, Vol. 121, 19-37, 2011.
doi:10.2528/PIER11030209

8. Donoho, D. L., "Compressed sensing," IEEE Trans. on Information Theory, Vol. 52, No. 4, 1289-1306, Apr. 2006.
doi:10.1109/TIT.2006.871582

9. Candes, E. J. and M. Wakin, "An introduction to compressive sampling," IEEE Signal Processing Magazine, Vol. 52, No. 4, 21-30, Mar. 2008.
doi:10.1109/MSP.2007.914731

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

11. Romberg, J., "Imaging via compressive sampling," IEEE Signal Processing Magazine, 14-20, Mar. 2008.
doi:10.1109/MSP.2007.914729

12. Baraniuk, R. and P. Steeghs, "Compressive radar imaging," IEEE Radar Conf., 128-133, Waltham, MA, Apr. 2007.

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

14. Varshney, K., M. Cetin, J. Fisher, and A. Willsky, "Sparse representation in structured dictionaries with application to synthetic aperture radar," IEEE Trans. on Signal Process., Vol. 56, No. 8, 3548-4561, Aug. 2008.
doi:10.1109/TSP.2008.919392

15. Patel, V., G. Easley, D. Healy, and R. Chellappa, "Compressed synthetic aperture radar," IEEE Journal of Selected Topics in Signal Processing , Vol. 4, No. 2, 244-254, Apr. 2010.
doi:10.1109/JSTSP.2009.2039181

16. 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

17. Wei, S.-J., X.-L. Zhang, and J. Shi, "Linear array SAR imaging via compressed sensing," Progress In Electromagnetics Research, Vol. 117, 299-319, 2011.

18. Ender, J., "On copressed sensing applied to radar," Elsevier Signal Process., Vol. 90, No. 5, 1402-1414, May 2010.

19. Candes, E. J., "The restricted isometry property and its implications for compressed sensing," C. R. Acad. Sci. Paris, Ser. I, 589-592, 2008.

20. Kreger, G., N. Gebert, and A. Moreira, "Unambiguous SAR signal reconstruction from nonuniform displaced phase center sampling," IEEE Geoscience and Remote Sensing Letters, Vol. 1, No. 4, 260-264, Oct. 2004.
doi:10.1109/LGRS.2004.832700


© Copyright 2014 EMW Publishing. All Rights Reserved