Title :
Compressive sensing for passive ISAR with DVB-T signal
Author :
Qiu, Wei ; Giusti, E. ; Bacci, A. ; Martorella, Marco ; Berizzi, F. ; Zhao, Hong Zhong ; Fu, Qiang
Author_Institution :
ATR Key Lab., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
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.
Keywords :
Fourier transforms; compressed sensing; digital video broadcasting; image resolution; optimisation; radar imaging; synthetic aperture radar; 2D-SL0 algorithm; DVB-T signal; Fourier based algorithm; ISAR image; compressive sensing; illuminator of opportunity; multiple DVB-T channel; passive ISAR; passive radar; range resolution; sparsity-driven optimization problem; television broadcast sources; Approximation algorithms; Bandwidth; Digital video broadcasting; Gratings; Image reconstruction; Imaging; Radar imaging;
Conference_Titel :
Radar Symposium (IRS), 2013 14th International
Conference_Location :
Dresden
Print_ISBN :
978-1-4673-4821-8