A Novel SAR Imaging Algorithm Based on Modified Multiple Measurement Vectors Model

CHEN Yichang; ZHANG Qun; YANG Ting; LUO Ying

doi:10.11999/JEIT151391

Volume 38 Issue 10

Oct. 2016

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(10): 2423-2429

CHEN Yichang, ZHANG Qun, YANG Ting, LUO Ying. A Novel SAR Imaging Algorithm Based on Modified Multiple Measurement Vectors Model[J]. Journal of Electronics & Information Technology, 2016, 38(10): 2423-2429. doi: 10.11999/JEIT151391

Citation:

CHEN Yichang, ZHANG Qun, YANG Ting, LUO Ying. A Novel SAR Imaging Algorithm Based on Modified Multiple Measurement Vectors Model[J]. Journal of Electronics & Information Technology, 2016, 38(10): 2423-2429. doi: 10.11999/JEIT151391

Citation:

PDF( 2308 KB)

A Novel SAR Imaging Algorithm Based on Modified Multiple Measurement Vectors Model

doi: 10.11999/JEIT151391

1.
(Institute of Information and Navigation, Air Force Engineering University, Xi&rsquo
2.

Funds:

The National Natural Science Foundation of China (61471386), The Postdoctoral Science Foundation of China (2015M570815), The Overall Innovation and Characteristic Industry Innovation Chain Project of Shaanxi Province (2015KTTSGY04-06)

Received Date: 2015-12-09
Rev Recd Date: 2016-05-03
Publish Date: 2016-10-19

Abstract

Abstract

Recently, the Compressed Sensing (CS) theory becomes the researching hot point in SAR imaging. The Multiple Measurement Vectors (MMV) model of CS theory can be used to effectively represent the jointly sparse signals, and it can obtain better performance than Single Measurement Vector (SMV) model. Because the SAR range profiles at different pulses have different sparse structures, which result in the MMV model can not be directly used in the scenario of synthetic aperture radar imaging. In this paper, a modified MMV model is proposed for SAR imaging, and the Range Migration (RM) effect is embedded into the proposed model. Correspondingly, a modified Orthogonal Matching Pursuit (OMP) algorithm is developed to obtain the high-resolution range profile. Experiments based on simulated and measured data demonstrate the validity of the proposed model and the algorithm.
- Synthetic Aperture Radar (SAR),
- Sparse reconstruction,
- Multiple Measurement Vectors (MMV) model,
- Range Migration (RM)

FullText(HTML)

References(20)

References

JUN Shi, ZHANG Xiaoling, and YANG Jianyu. Principle and methods on bistatic SAR signal processing via time correlation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(10): 3163-3178. doi: 10.1109/TGRS. 2008.920369.

SHEN Fangfang, ZHAO Guanghui, LIU Zicheng, et al. SAR imaging with structural sparse representation[J]. IEEE Journal of Selected Topocs in Applied Earth Observations and Remote Sensing, 2015, 8(8): 3902-3910. doi: 10.1109/JSTARS.2014.2364294.

BAMLER R. A comparison of Range-Doppler and wavenumber domain SAR focusing algorithm[J]. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(4): 706-713. doi: 10.1109/36.158864.

DONOHO D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306. doi: 10.1109/TIT.2006.871582.

邱伟, 赵宏钟, 陈建军, 等. 基于平滑范数的高分辨雷达一维成像研究[J]. 电子与信息学报, 2011，33(12): 2869-2874. doi: 10.3724/SP.J.1146.2011.00418.

QIU Wei, ZHAO Hongzhong, CHEN Jianjun, et al. Highresolution radar one-dimendional imaging based on smoothed norm[J]. Journal of Electronics Information Technology, 2011, 33(12): 2869-2874. doi: 10.3724/SP. J.1146.2011.00418.

BU Hongxia, TAO Ran, BAI Xia, et al. A novel SAR imaging algorithm based on compressed sensing[J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(5): 1003-1007. doi: 10.1106/LGRS.2014.2372319.

TELLO A M, LOPEZ D P, and MALLORQUI J J. A novel strategy for radar imaging based on compressive sensing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(12): 4285-4295. doi: 10.1109/TGRS.2010.2051231.

ONHON N O and CETIN M. A sparsity driven approach for joint SAR imaging and Phase error correction[J]. IEEE Transactions on Image Processing, 2011, 21(4): 2075-2088. doi: 10.1109/TIP.2011.2179056.

XIA Linuo, ZHU Daiyin, and JIANG Rui. A research on SAR autofocusing algorithms for compressive sensing technique [C]. IET International Radar Conference, Xi'an, 2013: 1-6.

GU Fu-fei, ZHANG Qun, CHI Long, et al. A novel motion compensating method for MIMO-SAR imaging based on compressed sensing[J]. IEEE Sensors Journal, 2015, 15(4): 2157-2165. doi: 10.1109/JSEN.2014.2371451.

CETIN M, STOJANOVIC I, ONHON N O, et al. Sparsity-driven synthetic aperture radar imaging: reconstruction, autofocusing, moving targets, and compressed sensing[J]. IEEE Signal Processing Magazine, 2014, 31(4): 27-40. doi: 10.1109/MSP.2014.2312834.

YANG Jiefang and ZHANG Yunhua. Novel compressive sensing-based Dechirp-Keystone algorithm for synthetic aperture radar imaging of moving target[J]. IET Radar, Sonar Navigation, 2015, 9(5): 509-518. doi: 10.1049/iet-rsn. 2014.0306.

CHEN J and HUO X. Theoretical results on sparse representations of multiple-measurement vectors[J]. IEEE Transactions on Signal Processing, 2006, 54(12): 4634-4643. doi: 10.1109/TSP.2006.881263.

YANG J, BOUZERDOUM A, TIVIVE F H C, et al. Multiple-measurement vector model and its application to through-the-wall radar imaging[C]. IEEE ICASS, Prague, Czech Republic, 2011: 2672-2675.

陈一畅, 张群, 陈校平, 等. 多重测量矢量模型下的稀疏步进频率SAR成像算法[J]. 电子与信息学报, 2014，36(12): 2986-2993. doi: 10.3724/SP.J.1146.2013.01831.

CHEN Yichang, ZHANG Qun, CHEN Xiaoping, et al. An imaging algorithm of sparse stepped frequency SAR based on multiple measurement vectors model[J]. Journal of Electronics Information Technology, 2014, 36(12): 2986-2993. doi: 10.3724/SP.J.1146.2013.01831.

TROPP J A, GILBERT A C, and STRAUSS M J. Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit[J]. Signal Processing, 2006, 86(3): 572-588. doi: 10.1016/j.sigpro.2005.05.030

TROPP J A and GILBERT A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. IEEE Transactions on Information Theory, 2007, 53(12): 4655-4666. doi: 10.1109/TIT.2007.909108.

CUMMING L G and WONG F H. Digital Processing of Synthetic Aperture Radar Data: Algorithm and Implementation[M]. MA: Artech House, 2005: 393-394.

Relative Articles

Supplements(0)

Cited By

Proportional views