High resolution ground moving target indication by synthetic aperture radar using compressed sensing

This paper addresses a novel GMTI algorithm for moving target detection and velocity estimation by the single-channel SAR system. In order to represent location and velocity of every moving target, a four-dimensional grid is introduced and GMTI problem is to find the elements in the above-mentioned 4-d grid related to moving targets. Clutter terms spread over all location grid cells but over only a few velocity grid cells, related to small velocities. Thus, the GMTI problem is not sparse and cannot be solved by compressive sensing reconstruction algorithms. A novel clutter suppression scheme is developed that sparsifies the problem. We reduce the amount of data storage and computational load by employing a measurement matrix. It is shown how the proposed clutter suppression scheme is significant for the high data load reduction case. An advantage of compressed sensing for this GMTI algorithm is to provide a high-resolution radar (HRR) system. Moreover, in practical situations where the clutter spectrum has a certain width in frequency, it is favorable to suppress an arbitrary number of clutter cells around zero Doppler. Our proposed subspace-based clutter cancellation method can suppress the stationary ground clutter as well as clutter up to higher velocities (like wind velocity) for applications like sea clutter cancellation.