针对两步加权最小二乘(two stage weighted least squares,TSWLS)算法在复杂场景下对运动辐射源定位不精确、观测站位置和目标位置的几何关系与精度相关的问题,提出一种基于泰勒展开与两步加权最小二乘联合的运动目标被动雷达质心无源定位算法.该方法首先利用两步加权最小二乘算法求解目标的位置与速度;再将所获得的目标参数作为泰勒展开的初始值构造定位误差方程,并通过迭代对目标寻优求解;最后利用联合算法和两步加权最小二乘算法分别获得估计值,对两次估计值进行质心定位得到最终结果.仿真实验表明,无论目标处于高速还是低速状态下,相较于传统的两步加权最小二乘算法和加权最小二乘(weighted least squares,WLS)算法,本文所提算法在鲁棒性和定位精度方面均有较大提高,且降低了观测站位置和目标位置几何关系对定位精度的影响.
A Joint Taylor Expansion-Least Squares and Centroid Localization Algorithm for Passive Radar of Moving Targets
In response to the imprecise localization of moving radiation sources in complex scenarios and issues related to the accuracy of the observation station's position and the geometric relationship with the target using the two stage weighted least squares(TSWLS)algorithm,we propose a passive radar centroid passive localization algorithm for moving targets based on Taylor expansion and the joint application of TSWLS.This method utilizes a TSWLS algorithm to determine the target's posi-tion and velocity.The obtained target parameters serve as initial values for Taylor expansion,con-structing the positioning error equation.Through iterative optimization,the algorithm refines and solves for optimal target parameters.The proposed algorithm and TSWLS independently provide esti-mations,with the final result obtained through centroid localization.Simulation experiments show that,regardless of target speed,in comparison with traditional methods,the presented algorithm sig-nificantly improves robustness and positioning accuracy while reducing sensitivity to geometric rela-tionships between the observation station and target.
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