Sparse arrays, MIMO, and compressive sensing for GMTI radar

This work proposes a radar combining four synergistic elements: space-time adaptive processing (STAP), random arrays, multiple-input multiple-output (MIMO) radar, and compressive sensing. STAP supports joint space-time processing for detecting moving targets in ground clutter. Large, random arrays are undersampled arrays that support improved angle-Doppler resolution and lower minimum detectable velocity (MDV), at the cost of higher sidelobes. MIMO provides further improvements in angular resolution and MDV. Compressive sensing algorithms are designed to cope with ambiguities introduced by undersampling. We propose an algorithm for target detection and analyze its performance for detecting, slow ground targets.