基于稳健代价函数的移动台非直达波定位方法

Robust Objective Function Location Method for Mitigation of NLOS Error

加权线性最小二乘定位算法在直达波传播条件下具有良好的定位性能,但是在非直达波传播导致的大误差环境下,基于均方代价函数最小化的常规方法未能有效抑制大误差对算法的影响,仍存在进一步改进的余地。本文提出一种基于非线性稳健代价函数的非直达波抑制方法,仿真结果表明,该方法能较好的抑制非直达波误差对测距定位性能的影响。

Though weighted least squares algorithm for mobile location performs well in case of line of sight propagation, conventional method based on minimizing mean square objective function could be improved further in case of non line of sight （NLOS） environment, because minimizing mean square objective function is used to deal with Gauss noise and cant effectively mitigate asymmetrically distributed measurement errors due to NLOS effect. In this paper, a robust objective function algorithm that can effectively mitigate big error is proposed to localize mobile station in different NLOS environments. Simulation result shows that the novel algorithm improves the performance of the weighted least squares algorithm based on time of arrival measurement significantly in different NLOS environments.