ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Mono-static SAR HRWS imaging algorithm of sea surface based on Markov chain
Received date: 2015-11-27
Revised date: 2016-03-15
Online published: 2016-03-22
Supported by
National Natural Science Foundation of China (61501498); Nature Science Foundation Research Program of Shaanxi Province (2015JM6306); Coordinator Innovative Engineering Project of Shaanxi Province (2015KTTSGY04-06)
This paper focuses on the problem of solving high resolution wide swath (HRWS) SAR imaging of sea surface using mono-static SAR and proposes a compressed sensing imaging method based on Markov chain. This method is inspired by the fact that target of sea surface usually owns a sparse distribution. Firstly, the wide swath sea scene is divided into several sub scenes. Secondly, a few pulses were used to generate a range profile, and the range profile is used to obtain the target number in each sub scenes. After that the radar scanning probability can be calculated using the target number. The radar then scan each sub scene based on the scanning probability. Thirdly, an improved compressed sensing algorithm is utilized to reconstruct each sub scenes; the whole wide swath image is united by putting all the sub scenes together. The proposed method can get a wide swath image without reducing the resolution of the radar. Finally, the effectiveness of the proposed method is proved by the simulation results.
NI Jiacheng , ZHANG Qun , GU Fufei , SUN Li , HUO Wenjun . Mono-static SAR HRWS imaging algorithm of sea surface based on Markov chain[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2016 , 37(12) : 3793 -3802 . DOI: 10.7527/S1000-6893.2016.0084
[1] 林月冠, 张冰尘, 田野, 等. 一种基于压缩感知的高分辨率宽测绘带合成孔径雷达成像算法[J]. 宇航学报, 2013, 34(1):106-112. LIN Y G, ZHANG B C, TIAN Y, et al. HRWS SAR imaging based on compressed sensing[J]. Journal of Astronautics, 2013, 34(1):106-112(in Chinese).
[2] WEN Q W, JING Y C. MIMO SAR using chirp diverse waveform for wide-swath remote sensing[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(4):3171-3185.
[3] WEN Q W. MIMO SAR imaging:Potential and challenges[J]. IEEE Transactions on Aerospace and Electronic Systems Magazine, 2013, 28(8):18-23.
[4] 武其松, 邢孟道, 刘保昌, 等. 面阵MIMO SAR大测绘带成像[J]. 电子学报, 2010, 38(4):817-824. WU Q S, XING M D, LIU B C, et al. Wide swath imaging with the plane array MIMO SAR system[J]. Acta Electronics Sinica, 2010, 38(4):817-824(in Chinese).
[5] 周伟, 刘永祥, 黎湘, 等. MIMO-SAR技术发展概况及应用浅析[J]. 雷达学报, 2014, 3(1):10-18. ZHOU W, LIU Y X, LI X, et al. Brief analysis on the development and application of multi-input multi-output synthetic aperture radar[J]. Journal of Radars, 2014, 3(1):10-18(in Chinese).
[6] JIE W, XIONG D L, CHI B D, et al. A novel scheme for ambiguous energy suppression in MIMO-SAR systems[J]. IEEE Transactions on Geoscience and Remote Sensing Letters, 2015, 12(2):344-348.
[7] SHUANG X Z, MENG D X, XIANG G X, et al. A robust imaging algorithm for squint mode multi-channel high-resolution and wide-swath SAR with hybrid baseline and fluctuant terrain[J]. IEEE Journal of Selected Topics Signal Processing, 2015, 9(99):1-16.
[8] MOORE R K, CLAASSEN J P, LIN Y H. Scanning spaceborne synthetic aperture radar with integrated radiometer[J]. IEEE Transactions on Aerospace and Electronic Systems, 1981, 17(3):410-420.
[9] GUARNIERI A M, PRATI C. ScanSAR focusing and interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 1996, 34(4):1029-1038.
[10] 万莉莉, 左伟华. 高分辨率宽测绘带Scan SAR压缩感知成像算法研究[J]. 信号处理, 2013, 29(4):466-473. WAN L L, ZUO W H. Research on high resolution wide swath scan SAR imaging algorithm based on compressive sensing[J]. Journal of Signal Processing, 2013, 29(4):466-473(in Chinese).
[11] 井伟, 张磊, 邢孟道, 等. 聚束式SAR的宽场景成像算法[J]. 电子学报, 2009, 37(3):470-475. JING W, ZHANG L, XING M D, et al. Algorithm for wide-swath spotlight SAR data processing[J]. Acta Electronics Sinica, 2009, 37(3):470-475(in Chinese).
[12] 杨东, 廖桂生, 朱圣棋, 等. 宽测绘带SAR成像的一种侧摆模式及其压缩感知处理方法[J]. 电子与信息学报, 2012, 34(11):2594-2600. YANG D, LIAO G S, ZHU S Q, et al. A lateral swing mode for wide swath SAR imaging based on the compressive sensing approach[J]. Journal of Electronics & Information Technology, 2012, 34(11):2594-2600(in Chinese).
[13] BOFILL P, ZIBULEVSKY M. Underdetermined blind source separation using sparse representation[J]. Signal Processing, 2001, 81(11):2353-2362.
[14] YANG J, ZHANG H, YAMAGUCHI H. GOPCE based approach to ship detection[J]. IEEE Transactions on Geoscience and Remote Sensing Letters, 2012, 9(6):1089-1093.
[15] YIN J, YANG J, XIE J, et al. An improved generalized optimization of polarimetric contrast enhancement and its application to ship detection[J]. IEICE Transactions on Communications, 2013, E96-B(7):2005-2013.
[16] 曾庆勋. 基于势函数与压缩感知的欠定盲源分离及应用[D]. 沈阳:辽宁大学, 2014:19-21. ZENG Q X. Under-determined blind source separation and its applications based on potential function and compressive sensing[D]. Shenyang:Liaoning University, 2014:19-21(in Chinese).
[17] JIAN F, ZONG B X, 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] DONOHO D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4):1289-1306.
[19] WEI S J, ZHANG X L, SHI J, et al. Sparse reconstruction for SAR imaging based on compressed sensing[J]. Progress in Electromagnetics Research, 2010, 109(4):63-81.
[20] 保铮, 邢孟道, 王彤. 雷达成像技术[M]. 北京:电子工业出版社, 2005:165-173. BAO Z, XING M D, WANG T. Radar imaging technology[M]. Beijing:Publishing House of Electronics Industry, 2005:165-173(in Chinese).
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