基于卡尔曼滤波和泰勒算法的超宽带室内定位方法

Ningmeng Lu, Zhi Gao
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摘要

为了解决室内复杂环境导致的非视距误差影响超宽带(UWB)技术定位精度的问题,本文提出了一种基于卡尔曼和泰勒算法的室内协同定位算法。首先,通过增量卡尔曼滤波对超宽带技术获得的测距值进行滤波,消除非近距离误差和测量系统误差的影响;然后,以最小二乘法(LSM)的计算结果为初始值,采用泰勒算法进行迭代,实现定位。实验结果表明,该方法能有效地消除定位系统中复杂环境的干扰,减小NLOS误差,提高定位精度。
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Ultra Wideband indoor positioning method based on Kalman filter and Taylor algorithm
So as to solve the problem that the non-line-of-sight (NLOS) error caused by the indoor complicated environment affects the positioning accuracy of Ultra Wideband (UWB) technology, an indoor collaborative positioning algorithm supported by Kalman and Taylor algorithm is proposed during this paper. Firstly, the ranging value obtained by UWB technology is filtered by incremental Kalman filter to eliminate the influence of NLOS error and measurement system error. Then, taking the calculation result of the least square method (LSM) as the initial value, the Taylor algorithm is used for iteration to realize the positioning. The experimental results show that the method can effectively eliminate the interference of complex environment in the positioning system, decrease the NLOS error and improve the precision of positioning.
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