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提出一种非视距环境中基于到达时间的移动定位优化算法。首先在基站端利用系统测量误差的先验知识判断到达时间测量值中是否存在非视距误差;然后通过加权正交多项式拟合对含有非视距误差的测量值进行修正,并利用有约束的加权优化算法对移动用户进行位置估计;最后对算法的定位误差性能进行仿真分析,并与视距环境中的最小二乘算法和有约束加权最小二乘算法的平均定位误差以及定位误差的克拉默.劳下界进行了比较。计算结果表明,提出的算法在非视距环境中能够得到较好的定位精度。
A mobile location optimization algorithm based on arrival time in non-line-of-sight environment is proposed. Firstly, we use the prior knowledge of system measurement error to judge whether there is a non-line-of-sight error in the measurement of arrival time. Then we correct the measurement value with non-line-of-sight error by weighted orthogonal polynomial fitting, Weighted optimization algorithm to estimate the location of mobile users. Finally, the performance of the algorithm is simulated and analyzed. The results show that the proposed algorithm is close to the least squares algorithm in sight environment and the average positioning error and Kramer The underworld has been compared. The calculation results show that the proposed algorithm can get better positioning accuracy in non-line-of-sight environment.