A Real-Valued Approximate Message Passing Algorithm for ISAR Image Reconstruction

摘要

Compressed sensing (CS) theory describes the signal using space transformation to obtain linear observation data selectively, breaking through the limit of the traditional Nyquist theorem. In this paper, we aim at accelerating the current approximate message passing (AMP) and propose an approach named real-valued AMP (RAMP) for faster and better inverse synthetic aperture radar (ISAR) imaging reconstruction. The azimuth dictionary is first processed with real. We then use matrix processing to solve the AMP vector iterative method, by utilizing the relation between the quantification of matrix product and the Kronecker product. The experimental results are presented to demonstrate the validity of this method.