Compressive Sensing-Based Coherent Signal Integration for Multistatic Microwave Radars

This paper addresses the problem of coherently integrating data from disparate receivers in a multistatic radar system when there are unknown phase relationships between them due to imperfect phase centre synchronisation. A novel approach is taken to reconstructing the radar scene in multiple dimensions using sparse estimation coupled with a technique to concurrently estimate the unknown phase offsets. The Pruned Orthogonal Matching Pursuit (POMP) technique was previously used to coherently integrate data from different, but co-located, narrowband radars to yields high range resolution (HRR) profiles for non-cooperative target recognition (NCTR) by increasing the overall effective bandwidth when they operate within different frequency bands. If the radars are physically separated with a large baseline, then coherent processing has the potential to yield not only accurate cross-range target location estimates for target tracking, but also high cross-range resolution profiles for NCTR by virtue of the large aperture induced by the separation of the radars. This paper demonstrates that for a general multistatic configuration the required coherency can be achieved in the unsynchronised data and that higher resolution in both range and cross-range can be attained than with conventional processing.