Target localization is an important problem in distributed multiple-input multiple-output (MIMO) radar systems. In this paper, a new algorithm using bistatic range measurements is developed for target localization in distributed MIMO radars. Unlike most existing schemes, the proposed algorithm firstly applies semidefinite relaxation to convert the maximum likelihood localization problem into a convex optimization problem. Subsequently, a novel procedure is devised to improve the solution accuracy of the convex optimization problem. Our scheme exhibits evidently better threshold behavior than the state-of-the-art approaches. Moreover, it does not require any initial estimate of the target position. Simulation results verify the superiority of the proposed algorithm over various existing methods.

目标定位是分布式多输入多输出 (MIMO) 雷达系统中的一个重要问题。在本文中，开发了一种使用双基地距离测量的新算法，用于分布式 MIMO 雷达中的目标定位。与大多数现有方案不同，所提出的算法首先应用半定松弛将最大似然定位问题转化为凸优化问题。随后，设计了一种新的程序来提高凸优化问题的求解精度。我们的方案比最先进的方法表现出明显更好的阈值行为。此外，它不需要对目标位置进行任何初始估计。仿真结果验证了所提出的算法优于现有的各种方法。