Bl GESPAR: A fast SAR imaging algorithm for phase noise mitigation
The performance of Synthetic aperture radar (SAR) imagery is often significantly deteriorated by the random phase noises arose from the atmospheric turbulence or frequency jitter of the transmit signal within SAR observations. The computational time of the traditional phase retrieval based SAR autofocus algorithms is sharply increased with the size of scene. In this paper, we recast the SAR imaging problem via the phase corrupted data as a special case of block based quadratic compressed sensing (BBQCS) problem. We propose a novel fast SAR imaging algorithm to recover the focused well SAR image from the phase corrupted data and reduce the computational time and memory requirement for several orders of magnitude. Experimental results show our proposed algorithm not only reduces the computational complex but also provides satisfactory reconstruction performance.
2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)