无需先验测量误差的定位节点选择方法

Selection method for localization node without priori measurement error

针对现有定位节点选择算法依赖先验测量误差的问题,研究了一种不依赖先验测量误差的时差与频差无源定位节点选择方法,该方法将两步加权最小二乘定位算法中目标估计误差协方差作为目标函数。在给定可用定位节点数目的情况下,通过引入一组布尔量构建关于目标函数为带约束的最小估计误差寻优问题,通过半定松弛技术将非凸问题转为半定规划问题进行求解,依据最小化问题特性,使得所提算法不依赖先验测量误差。仿真结果表明,不依赖测量误差的方法与穷举搜索法相比在定位性能上无太大差别;相比于穷尽搜索算法,所提方法复杂度低、实时性好。同时,仿真结果进一步表明在对运动目标定位过程中,及时调整定位节点组合的必要性。

In response to the problem of existing localization node selection algorithms relying on prior measurement error,this paper studies a passive localization node selection method for time difference of arrival and frequency difference of arrival(TDOA-FDOA)that does not rely on prior measurement error.This method takes the covariance of the target estimation error in the two-stage weighted least squares(TSWLS)localization algorithm as the objective function.Given the number of available positioning nodes,a minimum estimation error optimization problem with constraints on the objective function is constructed by introducing a set of boolean variables.The non-convex problem is transformed into a semi definite programming semi-definite programming(SDP)problem through semi-definite relaxation(SDR)technique for solution.Based on the characteristics of the minimization problem,the proposed algorithm does not rely on prior measurement error.The simulation results show that there is no significant difference in positioning performance between methods that do not rely on measurement error and exhaustive search methods;Compared to exhaustive search algorithms,the proposed method has lower complexity and better real-time performance.The simulation results further demonstrate the necessity of timely adjusting the combination of positioning nodes in the process of locating moving targets.