An algorithm based on the compressed sensing for near range two dimensional imaging

Abstract

Planar array two dimensional (2D) imaging is an important technology. It saves scanning time, but needs a large number of antenna elements. In order to save the cost, we hope to use less antennas to get the same (or better) image results. In this paper, we use sparse planar array and reconstruct the image by the two dimensional fast smoothed L0 (2D-SL0) algorithm. Paraxial Green function is used as sensing matrix. Comparisons of the algorithms based on 2D-SL0 algorithm and the matched filter processing (MFP) are demonstrated by means of numerical simulations. It is obvious that the imaging results by the 2D-SL0 algorithm is much clearer. And the focusing performance of the algorithm based on the 2D-SL0 algorithm is very well, even when we use the sparse antenna array.