CFAR detection for the complex approximated message passing reconstructed SAR image

Abstract

Complex approximated message passing (CAMP) is an iterative recovery algorithm for L1 regularization reconstruction which can achieve sparse and non-sparse estimations of original signal simultaneously. This paper demonstrates a CAMP-based synthetic aperture radar (SAR) image regularization reconstruction method along with a constant false alarm rate (CFAR) detection via the output non-sparse image of CAMP iterative algorithm. Compared with iterative thresholding algorithm (ITA) and orthogonal matching pursuit (OMP), the conventional L 1 regularization reconstruction techniques, it not only can improve SAR image performance, but also its non-sparse estimation retains a similar background statistical distribution as conventional matched filtering (MF)-based techniques, which can be used for CFAR detection efficiently. Simulated and experimental results validate the effectiveness of the designed CFAR detector for the CAMP reconstructed SAR image.