航空学报 > 2016, Vol. 37 Issue (2): 680-687   doi: 10.7527/S1000-6893.2015.0131

基于RIPless理论的层析SAR成像航迹分布优化方法

毕辉1,2, 张冰尘1, 洪文1   

  1. 1. 中国科学院电子学研究所微波成像技术重点实验室, 北京 100190;
    2. 中国科学院大学, 北京 100190
  • 收稿日期:2015-01-21 修回日期:2015-05-10 出版日期:2016-02-15 发布日期:2015-05-25
  • 通讯作者: 毕辉,男,博士研究生。主要研究方向:稀疏微波成像、层析合成孔径雷达成像。Tel:010-58887130,E-mail:bihui1991@163.com E-mail:bihui1991@163.com
  • 作者简介:张冰尘,男,博士,研究员,硕士生导师。主要研究方向:雷达系统与雷达信号处理、新体制雷达。Tel:010-58887124,E-mail:bczhang@mail.ie.ac.cn;洪文,女,博士,研究员,博士生导师。主要研究方向:三维微波成像等新概念、新方法。Tel:010-58887105,E-mail:whong@mail.ie.ac.cn
  • 基金资助:

    中国科学院创新团队国际合作伙伴计划

Track distribution optimization method based on TomoSAR via RIPless theory

BI Hui1,2, ZHANG Bingchen1, HONG Wen1   

  1. 1. Science and Technology on Microwave Imaging Laboratory, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
    2. University of Chinese Academy of Sciences, Beijing 100190, China
  • Received:2015-01-21 Revised:2015-05-10 Online:2016-02-15 Published:2015-05-25
  • Supported by:

    CAS/SAFEA International Partnership Program for Creative Research Team

摘要:

层析合成孔径雷达成像(TomoSAR)是通过同一观测区域不同入射角的多幅二维合成孔径雷达(SAR)图像在高程向进行孔径合成,从而实现三维成像。近年来,压缩感知(CS)被用于高程向稀疏场景的重建,高程向重建质量取决于观测矩阵的性质,而航迹分布是影响观测矩阵重构性能的重要因素。相比于度量观测矩阵重构性能的其他约束条件,RIPless理论具有有效、直观和计算简单等优点。提出了一种基于RIPless理论的压缩感知层析SAR成像航迹分布优化准则,从而在航迹数目一定的情况下,获取最优分布以实现高程向优化重建。最后,通过仿真和实验验证了所提优化准则的有效性。

关键词: 层析合成孔径雷达成像, 压缩感知, RIPless理论, 观测矩阵, 航迹优化

Abstract:

Synthetic aperture radar tomography(TomoSAR) applies measured repeat-pass SAR images to synthetize an aperture in the elevation direction, so as to achieve three-dimensional imaging. In recent years, compressive sensing(CS) has been used for elevation reconstruction for the sparse elevation distribution. The imaging quality of elevation of CS-based TomoSAR depends on the recovery property of measurement matrix, which is affected by the track distribution. Compared to other restrictions of recovery property for measurement matrix, RIPless theory is intuitionistic, effective and simple to calculate. In this paper, we propose a track distribution optimal criterion for CS-based TomoSAR via RIPless theory to optimize the distribution of flight tracks and achieve optimal reconstruction of elevation when the number of tracks is fixed. Simulation and experimental results validate the validity of the proposed optimization criterion.

Key words: synthetic aperture radar tomography, compressive sensing, RIPless theory, measurement matrix, track optimization

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