Post-processing phase noise mitigation performance comparison in a coherent distributed passive radar system

Phase noise in a radar system propagates through processing algorithms and affects the quality of the output radar data products by making targets harder to detect from noise and potentially confounding multiple targets. Usually referred to as autofocus algorithms, techniques for mitigating the effects of phase noise in these images have been proposed and studied in other applications including terrestrial telescope imaging and synthetic-aperture radar. We examine the effectiveness of autofocus algorithms as they attempt to mitigate phase noise in a coherent distributed passive radar system. We also propose an alternate technique based on deconvolution of power spectral densities, which has produced better results as well as requiring far less computation since no optimization problem exists within this method.