Weighted least squares algorithm for target localization in distributed MIMO radar

In this paper, we address the problem of locating a target using multiple-input multiple-output (MIMO) radar with widely separated antennas. Through linearizing the bistatic range measurements, which correspond to the sum of transmitter-to-target and target-to-receiver distances, a quadratically constrained quadratic program (QCQP) for target localization is formulated. The solution of the QCQP is proved to be an unbiased position estimate whose variance equals the Cramér-Rao lower bound. A weighted least squares algorithm is developed to realize the QCQP. Simulation results are included to demonstrate the high accuracy of the proposed MIMO radar positioning approach. HighlightsFormulate MIMO radar positioning as a quadratically constrained quadratic program (QCQP).Prove that the QCQP performance attains CRLB under small noise conditions.Realize the QCQP using weighted least squares.