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基于块稀疏的空间碎片群目标成像方法 被引量:7

Space Group Debris Imaging Based on Block-sparse Method
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摘要 针对星载雷达空间碎片群目标回波无法分离问题,该文利用回波在距离向表现出的块聚集特性,提出一种基于块稀疏的高分辨ISAR成像方法。基于块稀疏压缩感知理论,通过利用空间碎片群目标特性,抽取出各个碎片的高分辨1维距离像数据,并结合平动补偿和距离多普勒(RD)算法得到各碎片的ISAR像。在小样本条件下,该方法能够有效实现空间碎片的数据分离和高分辨ISAR成像。仿真实验表明,该方法的重构精度以及运算速度均优于非结构类的稀疏ISAR成像方法。 Space debris often appears in the form of groups, and the radar echoes overlap each other along the range direction. Utilizing the block structure, a high resolution space debris imaging method of ISAR is proposed based on the block-sparse Compressed Sensing (CS). This method can get high resolution 1-D range profile of every debris based on the block-sparse CS with the characteristics of space debris, and obtain the ISAR image combined with the translation compensation and the Range Doppler (RD) algorithm. The simulation results illustrate that the proposed method can achieve high resolution ISAR image with less reconstruction error and iterative number compared with the non-structure CS method under limited measurements.
出处 《电子与信息学报》 EI CSCD 北大核心 2015年第3期587-593,共7页 Journal of Electronics & Information Technology
基金 国家自然科学基金(61231017)和国家自然科学青年基金(61101249)资助课题
关键词 逆合成孔径雷达(ISAR) 压缩感知(CS) 空间碎片群成像 块稀疏 正交匹配追踪 Inverse SAR (ISAR) Compressed Sensing (CS) Group space debris imaging Block-sparsity Orthogonal matching pursuit
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  • 1白雪茹,孙光才,武其松,邢孟道,保铮.窄带雷达自旋目标成像[J].中国科学:信息科学,2010,40(11):1508-1518. 被引量:5
  • 2王洋,陈建文,刘中,刘爱芳.多运动目标ISAR成像方法研究[J].宇航学报,2005,26(4):450-454. 被引量:16
  • 3ENDER J, AMIN M G, FORNARO G, et al. Recent advances in radar imagin [From the Guest Editors] [J]. IEEE Signal Processing Magazine, 2014, 31(4), 15, 158.
  • 4CANDES E. The restricted isometry property and its implication for compressed sensing[J]. Comptes Rendus Mathematique, 2008, 346(9/10): 589-592.
  • 5BARANIUK R and STEEGHS P. Compressive radar imaging]C]. IEEE Radar Conference, Waltham, MA, 2007: 128-133.
  • 6HERMAN M A and STROHMER T. High-resolution radar via compressed sensing[J]. IEEE Transactions on Signal Processing, 2009, 57(6): 2275-2284.
  • 7ENDER J. On compressive sensing applied to radar[J]. Signal Processing, 2010, 90(5): 1402-1414.
  • 8POTTER L C, ERTIN E, PARKER J T, et al. Sparsity and compressed sensing in radar imaging[J]. Proceedings of the IEEE, 2010, 98(6): 1006-1020.
  • 9吴一戎.稀疏微波成像的理论、体制和方法研究[R].中国科学院,2010.
  • 10ROSSI M, HAIMOVICH A M, and ELDAR Y C. Spatial compressive sensing for MIMO radar[J]. IEEE Transactions on Signal Processing, 2014, 62(2): 419-430.

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