Reconstruction of Missing Samples in LFM Signals Using the Genetic Algorithm

Abstract

The reconstruction of non-stationary signals with missing samples is a particularly challenging topic. The compressed sensing (CS) reconstruction requires that signals exhibit sparsity in a transformation domain. We perform the CS reconstruction of the linear frequency modulated (LFM) signals with a common chirp rate, usually appearing in ISAR imaging. To this aim, we apply the genetic algorithm (GA).