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基于 TOF 结合残差加权的超宽带室内定位系统研究。

Research on UWB Indoor Positioning System Based on TOF Combined Residual Weighting.

机构信息

Key Laboratory of Grain Information Processing and Control (Henan University of Technology), Ministry of Education, Zhengzhou 450001, China.

Henan Key Laboratory of Grain Photoelectric Detection and Control, Henan University of Technology, Zhengzhou 450001, China.

出版信息

Sensors (Basel). 2023 Jan 28;23(3):1455. doi: 10.3390/s23031455.

Abstract

The performance of TDOA positioning based on UWB is limited by the hyperbolic characteristics of TDOA, especially for tags away from the hyperbolic asymptote. Aiming at this problem, a new UWB indoor positioning system is proposed. Firstly, TOF ranging is adopted to build the positioning equations; then the weighted centroid algorithm of four base stations is presented to compute the initial rough position of the tag; and the residual weighting is introduced to optimize the initial tag position; then, the corresponding nonlinear positioning equations, which will be algebraically transformed to one distribution function, are solved, and the optimal tag coordinates can be obtained by the Newton iteration method. Simulation experiments have verified the positioning reliability of the proposed algorithm under different noise environments and for different tag positions.

摘要

基于超宽带的 TDOA 定位性能受到 TDOA 双曲线特性的限制,尤其是对于远离双曲线渐近线的标签。针对这一问题,提出了一种新的超宽带室内定位系统。首先,采用 TOF 测距建立定位方程;然后提出了四基站加权质心法计算标签的初始粗略位置;并引入残差加权优化初始标签位置;然后,求解相应的非线性定位方程,将其代数转化为一个分布函数,通过牛顿迭代法得到最优标签坐标。仿真实验验证了所提出算法在不同噪声环境和不同标签位置下的定位可靠性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b277/9920415/1f70b29f1869/sensors-23-01455-g001.jpg

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