Reduced-complexity ML method for monostatic MIMO radar

A low complexity Maximum Likelihood (ML) method for monostatic MIMO radar has been proposed in this paper. In order to reduce the computational burden and maintain the accuracy of solution, the Beam Space Reduced Complexity ML algorithm (BS-RC ML) is developed for monostatic MIMO radar. The reduced-complexity ML method takes full advantage of the Reduced-dimension transformation and Beam-Space processing to reduce the dimension of the manifold vector from MN X K to B X K (B « MN). As the results, the lower computational cost and same angle estimation accuracy have been obtained. Some simulation results have been given to show the effectiveness of the proposed method. The strategy of reducing complexity in ML method can also be applied to some other angle estimation algorithms for MIMO radar.