基于Lagrange约束因子修正迭代初值的TDOA定位算法

TDOA Localization Algorithm Based on Lagrange Constraint Factor to Modify the Initial Value of Iteration

摘要: 对于TDOA定位法，不同的解算算法决定了不同的定位精度，传统的Taylor级数展开法对于初值选取的合适与否依赖性较强。为提高定位精度，本文在Taylor级数展开法的基础上提出了一种引入Lagrange约束因子修正初始位置误差的解算方法。仿真实验I表明，在同等仿真条件下，传统Taylor级数展开法的最优定位精度次于Chan算法的最优定位精度。仿真实验II表明，在星载观测平台组网个数分别为4、6时，本文提出的修正算法定位精度都优于传统的Chan算法、Taylor算法。

Abstract: For the TDOA positioning method, different algorithms determine different positioning accuracy, and the traditional Taylor series expansion method has a strong dependence on the suitability of the initial value selection. In order to improve the positioning accuracy, this paper proposes a method to correct the initial position error by introducing the Lagrange constraint factor on the basis of Taylor-series estimation. Simulation experiment I shows that under the same simulation conditions, the optimal positioning accuracy of the traditional Taylor series expansion method is lower than that of the Chan algorithm. Simulation experiment II shows that when the number of satellite observation platform networks is 4 and 6 respectively, the positioning accuracy of the modified algorithm proposed in this paper is better than the traditional Chan algorithm and Taylor algorithm.