Distributed MIMO Radar for Imaging and High Resolution Target Localization

Abstract

Abstract : 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; (b) finds a closed-form solution for the best linear unbiased estimator (BLUE) of target localization for coherent and non-coherent MIMO radars, providing a closed-form solution and a comprehensive evaluation of the performance of the estimator's MSE. This gives insight into the relation between sensor locations, target location, and localization accuracy through the use of the geometric dilution of precision (GDOP) metric; (c) present 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). (d) leveraging the concept of compressed sensing, it shows that by properly choosing a sufficient number of random sensors the ambiguities can be made arbitrarily small. Furthermore, the number of sensors can be trade with computational complexity, demonstrating that high resolution can be obtained with a relatively low number of randomly placed sensors