基于复数信息传递的结构稀疏宽角合成孔径雷达成像算法

蒋成龙; 张冰尘; 王正道; 洪文

doi:10.11999/JEIT141300

基于复数信息传递的结构稀疏宽角合成孔径雷达成像算法

doi: 10.11999/JEIT141300

基金项目:

国家973计划项目(2010CB731905)

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出版历程
- 收稿日期: 2014-10-11
- 修回日期: 2015-05-11
- 刊出日期: 2015-08-19

Group-sparse Complex Approximate Message Passing Algorithm for Wide Angle Synthetic Aperture Radar Imaging

摘要

摘要: 传统相关处理算法不能完全解决宽角合成孔径雷达(WASAR)成像中目标的散射特性随观测角度变化的问题。稀疏信号处理为该问题提供一种新思路，各向异性问题可以建模成欠定方程组。随角度增大，未知量的规模以观测孔径数目的线性规模增长，导致成功重建难度增大，甚至是重建失败。该文提出一种基于信息传递原理的宽角合成孔径雷达成像方法。根据宽角合成孔径雷达的观测几何及目标散射特性在不同角度之间存在的相关性，建立基于结构稀疏的成像模型；然后利用信息传递原理，提出基于结构稀疏复数信息传递(GCAMP)的成像算法求解该成像模型。仿真结果验证了该方法的有效性。
- 合成孔径雷达 /
- 宽角合成孔径雷达成像 /
- 各向异性散射特性 /
- 结构稀疏 /
- 信息传递
Abstract: Conventional matched filtering based algorithms are not sufficiently good at dealing with the anisotropic backscattering behavior of targets in Wide Angle SAR (WASAR) imaging. Sparse signal processing provides a new idea for this problem, the anisotropic problem is modeled as a group of under-determined linear equations. However, the scale of unknowns in the under-determined equations is in linear order of the number of the observation angle. As the observation angle increases, the anisotropic problem becomes more and more difficult to be solved, even failed for conventional sparse signal processing algorithms. This paper presents a Group- sparse Complex Approximated Message Passing (GCAMP) algorithm for WASAR imaging. Firstly, a group sparse based WASAR imaging model is provided according to the structured property of backscattering coefficients across different observation angles. Secondly, the GCAMP algorithm is derived from the imaging model using message passing theory. Results of simulation demonstrate the effectiveness of the proposed algorithm.
- SAR /
- Wide Angle SAR (WASAR) imaging /
- Anisotropic backscattering /
- Group sparse /
- Message passing

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参考文献(18)

[1]	Jakowatz C V, Wahl D E, Eichel P H, et al.. Spotlight-mode Synthetic Aperture Radar: A Signal Processing Approach[M]. Norwell, MA, US, Kluwer Academic Publishers, 1996: 62-94.
[2]	Allen M R, Phillips S A, and Sofianos D J. Wide-angle SAR-matched filter image formation for enhanced detection performance[C]. Proceedings of the International Society for Optics and Photonics in Substance Identication Technologies, Innsbruck, Austria, 1993: 381-387.
[3]	Chaney R D, Willsky A S, and Novak L M. Coherent aspect-dependent SAR image formation[C]. Proceedings of the International Society for Optics and Photonics in SPIE,s International Symposium on Optical Engineering and Photonics in Aerospace Sensing, Orlando, FL, USA, 1994, 256-274.
[4]	Moses R L, Potter L C, and Cetin M. Wide-angle SAR imaging[C]. Proceedings of the International Society for Optics and Photonics in Defense and Security, Orlando, FL, USA, 2004: 164-175.
[5]	Zhang B C, Hong W, and Wu Y R. Sparse microwave imaging: principles and applications[J]. SCIENCE CHINA Information Sciences, 2012, 55(8): 1722-1754.
[6]	Varshney K R, Cetin M, Fisher J W, et al.. Joint image formation and anisotropy characterization in wide-angle SAR[C]. Proceedings of the International Society for Optics and Photonics in Defense and Security Symposium, Orlando, FL, USA, 2006: 62370D.
[7]	Stojanovic I, Cetin M, and Karl W C. Joint space aspect reconstruction of wide-angle SAR exploiting sparsity[C]. Proceedings of the SPIE Defense and Security Symposium, Orlando, FL, USA, 2008: 697005.
[8]	Cetin M, Stojanovic I, Onhon 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.
[9]	Ash J, Ertin E, Potter L, et al.. Wide-angle synthetic aperture radar imaging: models and algorithms for anisotropic scattering[J]. IEEE Signal Processing Magazine, 2014, 31(4): 16-26.
[10]	林赟, 谭维贤, 洪文, 等. 圆迹SAR极坐标格式算法研究[J]. 电子与信息学报, 2010, 32(12): 2802-2807.
[11]	Lin Yun, Tan Wei-xian, Hong Wen, et al.. Polar format algorithm for circular synthetic aperture radar[J]. Journal of Electronics Information Technology, 2010, 32(12): 2802-2807.
[12]	洪文. 圆迹SAR成像技术研究进展[J]. 雷达学报, 2012, 1(2): 124-135.
[13]	Hong Wen. Progress in circular SAR imaging technique[J]. Journal of Radars, 2012, 1(2): 124-135.
[14]	Austin C D, Emre E, and Moses R L. Sparse signal methods for 3-D radar imaging[J]. IEEE Journal of Selected Topics in Signal Processing, 2011, 5(3): 408-423.
[15]	Donoho D L, Maleki A, and Andrea M. Message-passing algorithms for compressed sensing[J]. Proceedings of the National Academy of Sciences, 2009, 106(45): 18914-18919.
[16]	Maleki A, Laura A, Yang Z, et al.. Asymptotic analysis of complex LASSO via complex approximate message passing[J]. IEEE Transactions on Information Theory, 2013, 59(7): 4290-4308.
[17]	Fang J, Xu Z B, Zhang B C, et al.. Fast compressed sensing SAR imaging based on approximated observation[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(1): 352-363.
[18]	Jiang, C L, Zhang B C, Fang J, et al.. Efficient lq regularisation algorithm with range-azimuth decoupled for SAR imaging[J]. Electronics Letters, 2014, 50(3): 204-205.

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