Three-dimensional Imaging with Multi-aspect SAR Data

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.