MIMO radar based on reduced complexity compressive sampling

In their previous work, the authors considered a multiple-input multiple-output (MIMO) radar implemented by a set of randomly dispersed nodes within a small scale network. Exploiting the sparseness of targets in the angle-Doppler space, compressive sampling was exploited for obtaining joint angle-Doppler information on potential targets based on a small number of observations. That approach achieves the superior resolution of MIMO radar with far fewer samples than required by conventional approaches. However, it involves a discretization of the angle-Doppler space, and as the discretization step decreases in order to achieve high resolution, complexity increases. In this paper, a scheme to reduce the complexity of the aforementioned approach for the case of slowly moving targets is considered. The complexity reduction is achieved by decoupling angle and Doppler estimation. An approach is also proposed for identifying angle estimates that correspond to jammers.