Linear Array SAR Imaging Algorithm Using the Redundant Frame and Truncated SVD Based on Compressed Sensing

Abstract

For optimizing the linear array SAR (LASAR) system, the non-uniform linear arrays are usually used to reduce the number of array elements required. However, the data acquisition may be irregular sampling, which is impractical for traditional imaging algorithms. In this paper, based on compressed sensing (CS) approach for the non-uniform linear arrays, we proposed an imaging algorithm for the irregular sampling data. The contributions are twofold. Firstly, it employs the redundant frame to provide more samples and achieve a satisfactory resolution. Secondly, in order to decrease the massive calculations, it combines the truncated singular value decomposition (TSVD) and CS algorithm, while the imaging quality would not be contaminated. Both the theory analysis and simulation results are presented to demonstrate the validity of the proposed algorithm.