Compressive sensing???based algorithm for passive bistatic ISAR with DVB-T signals


Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting-terrestrial (DVB-T)-based passive radars. But, television broadcast-transmitted signals offer poor vary resolution for imaging purposes, as a result of they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer vary resolutions, signals composed of multiple DVB-T channels are needed. Problems arise, however, as a result of DVB-T channels are typically widely separated within the frequency domain. The gaps between channels produce high grating lobes in the image domain when Fourier-based mostly algorithms are used to make the ISAR image. During this paper, compressive sensing theory is investigated to address this drawback because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization drawback underneath the constraint of signal sparsity, passive ISAR pictures will be obtained with strongly reduced grating lobes. Each simulation and experimental results are shown to demonstrate the validity of the proposed approach.

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