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NLOS环境下基于Bootstrap方法的改进TOA定位算法研究

发布时间:2019-08-02 09:09
【摘要】:复杂的非视距传播(NLOS)环境带来的误差会严重影响定位算法的精度和稳健性,单纯的迭代优化算法面对大量的NLOS误差表现得并不理想。针对经典的TOA算法对非视距传播误差的敏感性问题,引入Bootstrap抽样及蒙特卡罗思想,提出了一种改进的TOA算法。利用随机化的思想对误差分布进行更加精确的识别,并通过随机模拟还原直线传播数据,结合牛顿迭代法对移动终端进行精确定位。实证分析证明,这种改进的TOA算法具有更高的精确性和稳健性。
[Abstract]:The error caused by the complex non-line-of-sight propagation (NLOS) environment will seriously affect the accuracy and robustness of the location algorithm. The simple iterative optimization algorithm is not ideal in the face of a large number of NLOS errors. In order to solve the sensitivity of classical TOA algorithm to non-line-of-sight propagation error, an improved TOA algorithm is proposed by introducing Bootstrap sampling and Monte Carlo ideas. The error distribution is identified more accurately by using the idea of randomization, and the straight line propagation data is reduced by random simulation, and the mobile terminal is accurately located by Newton iterative method. The empirical analysis shows that the improved TOA algorithm has higher accuracy and robustness.
【作者单位】: 山东科技大学数学与系统科学学院;
【基金】:全国统计科学研究重点项目《网络交易价格的大数据统计与数据挖掘方法研究》(2014LZ41)
【分类号】:TN92

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相关期刊论文 前10条

1 ;Robust location algorithm for NLOS environments[J];Journal of Systems Engineering and Electronics;2008年04期

2 ;Antenna Array Structures Effect on Water-Filling Capacity of Indoor NLOS MIMO Channel[J];The Journal of China Universities of Posts and Telecommunications;2005年03期

3 罗咏R,

本文编号:2522015


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