基于块压缩感知的SAR层析成像方法

王爱春 向茂生

王爱春, 向茂生. 基于块压缩感知的SAR层析成像方法[J]. 雷达学报, 2016, 5(1): 57-64. doi: 10.12000/JR16006
引用本文: 王爱春, 向茂生. 基于块压缩感知的SAR层析成像方法[J]. 雷达学报, 2016, 5(1): 57-64. doi: 10.12000/JR16006
Wang Aichun, Xiang Maosheng. SAR Tomography Based on Block Compressive Sensing[J]. Journal of Radars, 2016, 5(1): 57-64. doi: 10.12000/JR16006
Citation: Wang Aichun, Xiang Maosheng. SAR Tomography Based on Block Compressive Sensing[J]. Journal of Radars, 2016, 5(1): 57-64. doi: 10.12000/JR16006

基于块压缩感知的SAR层析成像方法

doi: 10.12000/JR16006
基金项目: 

国家发改委卫星及应用产业发展专项项目发改委高技【2012】2083号

详细信息
    作者简介:

    王爱春(1981-),男,内蒙古和林格尔县人,中国资源卫星应用中心工程师,中国科学院电子学研究所在读博士生,研究方向为多基线干涉SAR处理方法及应用。E-mail:wangaichun@cresda.com向茂生(1964-),男,中国科学院电子学研究所研究员,博士生导师,研究方向为干涉合成孔径雷达系统技术和方法。E-mail:xms@mail.ie.ac.cn

    通讯作者:

    王爱春wangaichun@cresda.com

SAR Tomography Based on Block Compressive Sensing

Funds: 

National Development and Reform Commission Satellite and Application Development Projects【2012】2083

  • 摘要: 基于压缩感知(Compressive Sensing, CS)的SAR层析成像方法(SAR Tomography, TomoSAR),虽然实现了对目标的3维重构,但对于具有结构特性的目标其重构性能较差。针对这一问题,该文提出了采用块压缩感知(Block Compressive Sensing, BCS)算法,该方法首先在CS方法基础上将具有结构特性的目标信号重构问题转化为BCS问题,然后根据目标结构特性与雷达参数的关系确定块的大小,最后对目标进行块稀疏的l1/l2范数最优化求解。相比基于CS的SAR层析成像方法,该方法更好地利用了目标的稀疏特性和结构特性,其重构精度更高、性能更优。仿真数据和Radarsat-2星载SAR实测数据的试验结果验证了该方法的有效性。

     

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出版历程
  • 收稿日期:  2016-01-11
  • 修回日期:  2016-01-27

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