压缩感知联合稀疏孔径自聚焦的多站无源雷达成像

doi:10.3969/j.issn.0255-8297.2014.02.005

Abstract

Abstract: In this paper, passive multistatic radar imaging based on compressed sensing joint sparse aperture autofocus is presented. The method uses a point spread function of the different opportunistic illuminator to construct a reasonable sparse basis matrix, and turns the point-enhanced problem into an optimization problem by using the lp norm method. Meanwhile an optimization problem in terms of phase error is established. The quasi-Newton method with a phase error update scheme is used to obtain the increment of phase error. The simulation shows good performance of this method at small rotating angle and in the presence of phase error.

Key words: passive radar imaging, multistatic radar, sparsity, compressed sensing (CS), autofocus

CLC Number:

TN957.52

WU Hao, SU Wei-min, GU Hong. Passive Multistatic Radar Imaging Based on Compressed Sensing Joint Sparse Aperture Autofocusing[J]. Journal of Applied Sciences, 2014, 32(2): 141-148.

References

[1] 杨博，王丰华，周一宇，黄知涛. 空基辐射源非合作探测系统目标定位[J]. 应用科学学报，2010, 28(03): 246-253.

YANG Bo, WANG Fenghua, ZHOU Yiyu, HUANG Zhitao. Location of space-based emitter in non-cooperative monitoring system[J]. Journal of Applied Sciences. 2010, 28(03): 246-253. (in chinese)

[2] WU Y, MUNSON D C. Multistatic synthetic aperture imaging of aircraft using reflected television signals[C]//Orlando, FL, United states, IEEE International Conference on Image Processing, 2001: 1-12.

[3] 张馨文，王俊. 基于多电视台子孔径综合的无源雷达成像算法[J]. 电子与信息学报，2007, 29(03): 528-531.

ZHANG Xinwen, WANG Jun. Passive radar imaging algorithm based on sub-apertures synthesis of multiple television stations[J]. Journal of Electronics & Information Technology. 2007, 29(03): 528-531. (in chinese)

[4] WANG L, YARMAN C E, YAZICI B. Doppler-hitchhiker: A novel passive synthetic aperture radar using ultranarrowband sources of opportunity [J].IEEE Transactions on Geoscience and Remote Sensing, 2011: 3521-3537.

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

[6] 王妮娜，桂冠，张治,唐恬. 基于压缩感知的MIMO系统稀疏信道估计[J]. 应用科学学报. 2011, 29(04): 347-352.

WANG Nina, GUI Guan, ZHANG Zhi, TANG Tian. Compressed sensing based sparse channel estimation in MIMO systems[J]. Journal of Applied Sciences, 2011, 29(04): 347-352.(in chinese)

[7] 吴昊，苏卫民，陈刚，顾红. 基于压缩感知的多基地无源雷达成像算法[J]. 宇航学报，2012(11): 1681-1689.

WU Hao, SU Weimin, CHEN Gang, GU Hong. Passive multistatic radar imaging algorithm based on compressed sensing [J]. Journal of Astronautics, 2012(11): 1681-1689.(In Chinese)

[8] LIU K, MUNSON D C. Autofocus in multistatic passive SAR imaging[C]//Las Vegas, NV, IEEE International Conference on Acoustics, Speech and Signal Processing, 2008: 1277-1280.

[9] WAHL D E, EICHEL P H, GHIGLIA D C, JAKOWATZ C V. Phase gradient autofocus - a robust tool for high resolution SAR phase correction[J]. IEEE Transactions on Aerospace and Electronic Systems, 1994, 30(3): 827-835.

[10] XI L, GUOSUI L, NI J. Autofocusing of ISAR images based on entropy minimization[J]. IEEE Transactions on Aerospace and Electronic Systems, 1999, 35(4): 1240-1252.

[11] TIAN J, SUN J, HAN X, ZHANG B. Motion compensation for compressive sensing SAR imaging with autofocus[C]//Piscataway, NJ, USA: IEEE, 2011: 1564-1567.

[12] SAMADI S, CETIN M, MASNADI-SHIRAZI M A. Sparse representation-based synthetic aperture radar imaging [J]. IET Radar, Sonar and Navigation, 2011, 5(2): 182-193.

[13] POTTER L C, ERTIN E, PARKER J T, CETIN M. Sparsity and compressed sensing in radar imaging [J]. Proceedings of the IEEE, 2010, 98(6): 1006-1020.

Passive Multistatic Radar Imaging Based on Compressed Sensing Joint Sparse Aperture Autofocusing

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 8

Recommended Articles

Metrics

Comments

[1]	MA Xin, WU Yun, LU Zeguang. Collaborative Filtering Recommendation Model Based on Hybrid Neural Network [J]. Journal of Applied Sciences, 2020, 38(3): 478-487.
[2]	XIONG Yan-wei, ZHANG Jian-hua, ZHANG Ping. Design of Channel Emulator for Wideband MIMO Systems [J]. Journal of Applied Sciences, 2014, 32(3): 229-236.
[3]	JIA Ying-biao, FENG Yan, YUAN Xiao-ling, WEI Jiang. Block Compressed Sensing Sampling and Reconstruction Using Spectral Prediction for Hyperspectral Images [J]. Journal of Applied Sciences, 2014, 32(3): 281-286.
[4]	DENG Zhen-miao, YE Lin-mei, FU Mao-zhong, ZHANG Yi-xiong. Radar Super-Resolution Imaging Based on Compressive Sensing [J]. Journal of Applied Sciences, 2014, 32(2): 133-140.
[5]	YE Xin-rong1,2, ZHU Wei-ping1, MENG Qing-min1. Sparse Channel Estimation Based on Compressed Sensing for MIMO-OFDM Systems [J]. Journal of Applied Sciences, 2013, 31(3): 245-251.
[6]	LANG Li-ying, XIA Fei-jia. Zero-Norm Sparse Coding in Face Recognition [J]. Journal of Applied Sciences, 2012, 30(3): 281-286.
[7]	WANG Ni-na1, GUI Guan2;3, ZHANG Zhi1, TANG Tian1. Compressed Sensing Based Sparse Channel Estimation in MIMO Systems [J]. Journal of Applied Sciences, 2011, 29(4): 347-352.
[8]	WEI Chong-yu, XU Shan-jia, WANG Dong-jin. Target Location and Speed Estimation Based on a Multistatic Radar System Using the Maximum Likelihood Approach [J]. Journal of Applied Sciences, 2000, 18(2): 117-121.