多站测向交叉定位的加权最大似然估计算法及其精度分析

Algorithm of Weighted Maximum Likelihood Estimation in Multistation DF Crossing Localization and Its Accuracy Analysis

为解决测向交叉定位中测向误差的标准方差受目标区域非均匀环境的影响,提出加权最大似然估计(WMLE)算法。该算法将目标距离引入到MLE算法当中,通过构造加权向量来弥补测向误差的标准方差随目标距离增加而增大的影响。理论分析表明,改进后的WMLE算法可进一步提高多站测向交叉定位系统的定位精度。

In Direction-Finding （DF） crossing localization, the standard deviation of DF error is influenced by the nonuniform environment of the target area. To solve the problem, we proposed a Weighted Maximum Likelihood Estimation （WMLE） algorithm. In this algorithm, the effect of the target distance was introduced into Maximum Likelihood Estimation （MLE）. A weighted vector was constructed to control and compensate for the standard deviation of the DF error increasing with the target distance. Theoretical analysis showed that the algorithm of WMLE can further improve the accuracy of the multi-station DF crossing localization.