Distributed MIMO Radar for Imaging and High Resolution Target Localization

The Air Force Office of Scientific Research supported the research on MIMO radar carried out at the New Jersey Institute of Technology during the period from April 2009 to November 2011 under the agreement number FA9550-09-1-0303. The purpose of this report is to summarize the proceedings and findings of the studies supported by this agreement. The report addresses two broad topics: (i) performance bounds for localization, (ii) applications of compressive sensing methods to target localization. Two types of bounds were developed for target localization with MIMO radar: Cramer-Rao bound for high signal to noise ratio (SNR), and Ziv-Zakai bound that effective for a wide range of SNRs. More specifically, the research supported by the grant: (a) develops the Cramer-Rao lower bound (CRLB) of the target localization estimation error for the general case of MIMO radar with multiple waveforms with non-coherent and coherent observations [1]; (b) finds a closed-form solution for the best linear unbiased estimator (BLUE) of target localization for coherent and non-coherent MIMO radars [2], providing a closed-form solution and a comprehensive evaluation of the performance of the estimator’s mean square error; (c) presents an analysis on the ambiguity arising in the high resolution localization due to sidelobe characteristics of the MIMO system using the Ziv-Zakai Bound (ZZB) [3]; (d) leverages the concept of compressed sensing to show that by properly choosing a sufficient number of random sensors [4], [5] it is possible to perform highly accurate target localization with far fewer sensors than other localization methods. Furthermore, the number of sensors can be traded-off with computational complexity,demonstrating that high resolution can be obtained with a relatively low number of randomly placed sensors.