Target estimation using compressive sensing for distributed MIMO radar

Distributed Multiple Input Multiple Output (MIMO) radar systems enable viewing the targets from different angles, thereby providing spatial diversity gain. In this paper, we propose an approach to accurately estimate the parameters (position, velocity) of multiple targets using such systems from fewer number of samples by employing compressive sensing. We also introduce a new metric to analyze the performance of the radar system. We show the improvement in performance over conventional Single Input Single Output (SISO) radar systems due to the spatial diversity offered by MIMO radar. We also demonstrate that the sampling rates can be significantly reduced by using compressive sensing at the receivers.