摘要
利用多角度SAR数据实现目标高分辨率3维成像对雷达自动目标识别具有重要价值。该文在目标散射稀疏性前提下提出了基于压缩感知的多角度SAR 3维成像方法。文章首先论证多角度SAR测量能够改善测量矩阵的互不相关性。然后根据互不相干影响因素分析,合理选择目标离散间隔构造多角度SAR测量矩阵。最后利用分段正交匹配追踪算法实现目标向量的稀疏重构。该文算法不仅改善了高度分辨率,而且克服了多角度SAR空间采样不连续导致的高旁瓣问题。实验验证了该算法的可行性和稳定性。
Carrying out 3-D imaging with multi-aspect SAR data is impressive to radar Automatic Target Recognition （ATR）. This paper presents a multi-aspect SAR 3-D imaging technique based on compressive sensing, provides that the target scattering field is sparse. Firstly, it is validated that by multi-aspect SAR measurements the mutual incoherence of measurement matrix is improved. Secondly, the measurement matrix is constructed by carefully selecting the sampling interval in the space domain based on the analysis of mutual incoherence. Finally, the object sparse vector is reconstructed with Stagewise Orthogonal Matching Pursuit （StOMP） algorithm. The proposed method not only improves the resolution of elevation dimension, but also conquers the acute lobe-side resulted from incontinuous sampling. Numerical experiments are given to illustrate the effectiveness and robustness of the proposed method.
出处
《电子与信息学报》
EI
CSCD
北大核心
2013年第10期2467-2474,共8页
Journal of Electronics & Information Technology
基金
国家自然科学基金(61171135
60972120)资助课题
关键词
多角度SAR数据
3维雷达成像
压缩感知
稀疏信号
Multi-aspect SAR
Three-dimensional radar imaging
Compressive Sensing （CS）
Sparse signal
