Sparse passive radar imaging based on digital video broadcasting satellites using the MUSIC algorithm

This paper investigates the passive radar imaging system which exploits digital video broadcasting (DVB) satellites as opportunity illuminators. Firstly, we establish the imaging model and then analyze the imaging performance in the wavenumber domain. Because of the practical limitations, we are likely to get an undersampled wavenumber domain coverage so that traditional imaging methods such as matched filter (MF) would fail to provide good imaging performance. Therefore, we consider to use the sparse recovery techniques to achieve good inversion results. However, the compressive sensing (CS) imaging methods would be severely affected when off-grid scatterers exist. According to the theories of the Xampling and the finite rate of innovation (FRI), we propose a high-resolution sparse imaging method to overcome the problems above, which is based on the multiple signal classification (MUSIC) algorithm. Simulation results verify the effectiveness of the proposed method.