Tomography synthetic aperture radar imaging based on extended block orthogonal matching pursuit algorithm

Abstract

The compressed sensing (CS)-based methods for tomography synthetic aperture radar (SAR) imaging have a good performance in the case of a large number of baselines. Unfortunately, for the current tomography SAR, the baselines are obtained in repeat-pass mode from a large number of parallel passes in the same scene. That is expensive and can be severely affected by temporal decorrelation. And the performance of CS-based methods degrades rapidly with the decrease of the number of baselines. Inspired by the block-sparsity theory, an extended block orthogonal matching pursuit algorithm by using the weighted operation and a new column-block selection strategy is proposed for tomography SAR imaging. By using neighboring pixels information in reconstruction, the proposed method can improve the performance of CS-based methods in the case of strong noise and a small number of baselines. Experimental results confirm the effectiveness of the proposed method.