基于自适应UKF的UWB/PDR行人定位系统

doi:10.16180/j.cnki.issn1007-7820.2023.06.007

摘要/Abstract

摘要：

UWB(Ultra-Wide Band)无线通讯技术在室内导航定位领域获得了广泛的应用,然而基于UWB的行人定位系统在复杂室内环境下的稳定性不佳,导致定位误差增大。为了解决这一问题,文中提出了一种基于自适应无迹卡尔曼滤波(Unscented Kalman Filter,UKF)的UWB/PDR(Pedestrian Dead Reckoning)行人定位系统。该系统利用无迹卡尔曼滤波算法将PDR模型与UWB的定位信息进行融合,以得到最优位置估计,随后利用UWB定位与PDR系统所获得的步长差概率密度函数来计算定位点的非视距评估概率,并将评估结果作用于系统的自适应噪声调整,以此提高系统对环境的适应性。实验验证结果表明,该系统可有效降低复杂环境下定位误差,提高行人定位结果的精度和稳定性,平均定位精度达到10 cm以内。

关键词: 室内导航, 行人定位, UWB, PDR, UKF, 非视距, 噪声调整

Abstract:

Ultra-Wide Band(UWB) wireless communication technology has been widely used in the field of indoor navigation and positioning. However, the stability of pedestrian positioning systems based on UWB is not good in complex indoor environments, resulting in increased positioning errors. In order to solve this problem, this study proposes a Pedestrian Dead Reckoning(UWB/PDR) system based on adaptive Unscented Kalman Filter(UKF). The system uses the UKF algorithm to fuse the PDR model and the UWB positioning information to obtain the optimal position estimate. The probability density function of the step difference obtained by the UWB positioning and the PDR system is used to calculate the non-line of sight evaluation probability of the positioning point, and the evaluation result is applied to the adaptive noise adjustment of the system to improve the adaptability of the system for the environment. Experimental verification results show that the system can effectively reduce the positioning error in a complex environment, improve the accuracy and stability of the pedestrian positioning results, and its average positioning accuracy is less than 10 cm.

Key words: indoor navigation, pedestrian positioning, UWB, PDR, UKF, NLOS, noise adjustment

中图分类号:

TP393

卢敏龙,郭崴,张轩雄. 基于自适应UKF的UWB/PDR行人定位系统[J]. 电子科技, 2023, 36(6): 41-49.

LU Minlong,GUO Wei,ZHANG Xuanxiong. UWB/PDR Pedestrian Localization System Based on Adaptive UKF[J]. Electronic Science and Technology, 2023, 36(6): 41-49.

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定位方法	平均误差/m	最大误差/m
自适应UKF	0.076	0.247
UKF	0.122	0.288
KF	0.147	0.392
UWB定位	0.171	0.773
PDR定位	0.275	0.941