分布式MIMO雷达的目标定位

针对多输入多输出雷达系统,研究了目标定位问题,并提出基于双基测距的分布式多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达的目标定位算法。首先,通过引入多余参数和这些参数与未知目标定位的关系,将目标定位问题转化为约束二次规划(Quadratically Constrained Quadratic Programming,QCQP)问题,然后,考虑到QCQP问题是非凸和NP-Hard,再将每个非凸约束近似为线性约束,最终QCQP问题就转化为线性约束二次规划(Linearly Constrained Quadratic Programming,LCQP)问题。最后,利用迭代约束权重最小二乘(Iterative Constrained Weighted Least Square,ICWLS)算法求解LCQP问题。实验数据表明,提出的ICWLS算法能够收敛于一个最优值。

Target Localization in Distributed MIMO Radar

The problem of determining the target position in multiple-input multiple-output (MIMO) radar system is studied in this letter. A target localization algorithm in distributed MIMO radar is proposed based on bistatic range measurements. By introducing the nuisance parameters and taking the relationship between these parameters and the unknown target position into consideration, the target localization problem is firstly formulated as a QCQP problem. Since the constraints are nonconvex and NP-hard, we recursively approximate each nonconvex constraint as a linear constraint. So we convert the QCQP problem to a linearly constrained quadratic programming (LCQP) problem. Finally, an iterative constrained weighted least squares (ICWLS) algorithm is used to solve the problem. The simulation results show that the proposed iterative CWLS method is able to converge at an optimal solution.