Adventures in compressive sensing based MIMO radar

Abstract

While radar has been around for many decades, novel developments in recent years have led to significant breakthroughs as well as to exciting new mathematical challenges. In this chapter, we consider a multiple-input-multiple-output (MIMO) radar system. Using sparsity as a key ingredient of our approach and tools from compressive sensing, we derive a mathematical framework for the imaging of targets in the azimuth-range-Doppler domain. Our analysis comprises uniformly spaced linear arrays with random waveforms, as well as random sensor arrays with deterministic waveforms. We also derive results that do not require the “on-the-grid” assumption often used in compressive sensing radar. Algorithmic aspects and numerical simulations are presented as well.