MMW compressed sensing target reconstruction based on AMPSO search algorithm

Abstract

ABSTRACT Introducing compressed sensing theory into the millimeter-wave near-field holographic imaging algorithm, it can break the Nyquist sampling limit, reconstruct the compressed echo signal, and invert the target image. In the reconstruction process, there are defects such as missing target key information, excessive invalid search volume and so on. Aiming at this problem, an adaptive multi-extreme particle swarm optimization (AMPSO) algorithm is proposed. Its advantages are that it can retain more target information, search for more extreme values, and improve the convergence speed. At the same time, the search probability in the strong scattering area is also increased, the search time is avoided in the noise area, and the number of extreme points is adjusted on a global scale. The effectiveness of the algorithm is verified by simulation and actual measurement of multiple types of targets under different experimental conditions.