Efficient Solutions for MIMO Radar Localization Under Unknown Transmitter Positions and Offsets
Xiaoping Wu, Yupeng Liu, Xuefeng Zhu, Lufeng Mo
Abstract
Two efficient solutions are proposed for the localization problem of an object in multiple-input multiple-output (MIMO) radar systems, when the transmitter positions and offsets are unknown. The localization problem is first recast into a convex form by applying the semidefinite relaxation (SDR) technique, the solution of which converges to global optimum. We also propose a closed-form solution warranting global convergence, in which the object position is estimated by two stages. In the stage-one solution, the auxiliary variables are introduced to transform the nonlinear problem into a linear form. The stage-two solution is further designed to refine the estimates obtained from the stage-one solution. The minimum number of receivers and the complexity are also analyzed for the proposed solutions. The simulated results show that the SDR and closed-form solutions provide good estimates for the object position and transmitter positions. Their performance can sufficiently approach the Cramér-Rao Lower Bound (CRLB) accuracy at the high signal-to-noise ratio (SNR).