基于压缩感知的多角度合成孔径雷达成像

多角度合成孔径雷达（syntheticapertureradar，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（stagewiseorthogonalmatchingpursuit，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-aspect SAR imaging based on compressive sensing

Multi-aspect synthetic aperture radar （SAR） imaging is an important technique for synthesizing multi-aspect SAR data or information. Achieving multi-aspect SAR imagery is invaluable for resolution improvement, radar object visualization, classification and automatic object recognition （ATR）. However, achieving multi-aspect SAR imaging is challenging because of the diversity of space sampling positions and the transmission of signal waveforms. In this study, a new method, based on the model of a multi-aspect SAR data collection, is proposed to achieve multi-aspect SAR imaging using compressive sensing and sparse reconstruction theory. First, the factors which dominate the performance of the measurement matrix were studied. It was found that the distribution of space sampling and the carrier frequency of the transmission signal were the key factors dominat- ing the mutual coherence （MC） of the measurement matrix. The object sampling space was also a key factor in determining the robustness and resolution of multi-aspect SAR imaging. Second, the measurement matrix for the multi-aspect SAR was constructed, depending on previous analysis, by careful selection of the parameters and sampling of the object. Third, the stage-wise orthogonal matching pursuit （STOMP） algorithm was applied to achieve multi-aspect SAR imaging. This algorithm was effective in solving high-dimensional ill-posed equations. Extensive experiments validated the feasibility and stability of the proposed algorithm.