Compressive sensing for passive ISAR with DVB-T signal

As recently demonstrated, ISAR images can be obtained by using DVB-T based Passive radars. Television broadcast sources offer, however, very poor range resolution for imaging purposes, as illuminators of opportunity(IOs) transmits signals with lower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, a signal composed of multiple DVB-T channels is required. Problems arise however, when the DVB-T channels are spectrally separated. The gaps between DVB-T channels may degrade the image significantly when Fourier based algorithms are used to form the ISAR image. In this paper, the Compressive Sensing (CS) theory is investigated to address this problem. Specifically, a 2D-SL0 algorithm is used to solve a sparsity-driven optimization problem. Simulation based results are then used to validate the proposed algorithm.