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多角度合成孔径雷达(synthetic aperture radar,SAR)成像是实现多SAR信息融合的重要方式,对提高成像分辨率,重构目标轮廓进而提高雷达目标检测或分类性能具有基础性价值.由于各传感器发射信号和测量位置的多样性,实现多角度SAR成像具有挑战性.如何在噪声干扰情况下快速实现多角度SAR成像是一个新问题.本文建立了基于压缩感知的多角度SAR测量模型.通过对测量矩阵的分析,证明多角度SAR测量角度范围、发射信号载频和空间采样位置是影响成像性能的关键因素,研究了目标空间离散间隔对成像质量和分辨率的影响.以上述分析为基础,本文对多角度SAR发射信号载频和测量位置进行设计,构建满足约束等距性的测量矩阵.针对测量矩阵阶次较高的问题,文章提出用分段正交匹配追踪(stagewise orthogonal matching pursuit,StOMP)进行模型求解,在测量矩阵欠定严重的情况下,该算法可以迅速求得模型最优稀疏解.在实验环节,通过分析多角度SAR参数对成像性能的影响,进一步验证了本文结论.实验验证了模型和相应求解算法的有效性和鲁棒性.
Multi-angle Synthetic Aperture Radar (SAR) imaging is an important way to realize multi-SAR information fusion, which is of fundamental value to improve imaging resolution, reconstruct the target contour and then improve the detection or classification performance of radar targets.Because each sensor launches Signal and location of measurement diversity, to achieve multi-angle SAR imaging is challenging.How to quickly achieve multi-angle SAR imaging under noise interference is a new problem.This paper established a multi-angle SAR measurement model based on compressed sensing. The analysis of the matrix shows that the angular range of multi-angle SAR measurement, the carrier frequency of the transmitted signal and the location of the spatial sampling are the key factors that affect the imaging performance, and the influence of the discrete distance of the target space on the imaging quality and resolution is studied.Based on the above analysis, The carrier frequency and measurement position of multi-angle SAR transmitting signal are designed to build the measurement matrix which satisfies the constraint equidistance.In order to solve the problem that the measurement matrix order is higher, the paper proposes to use the stagewise orthogonal matching pursuit (StOMP ) To solve the model, the algorithm can be used when the measurement matrix is underdetermined And the optimal sparse solution of the model is obtained quickly.In the experimental part, the conclusion of this paper is verified by analyzing the influence of the multi-angle SAR parameters on the imaging performance.The validity and robustness of the model and the corresponding algorithm are verified by experiments.