UWB/IMU combined positioning method based on improved SHKF algorithm

被引：0

作者：

Huang W. ^{[1
]}

Mei Y. ^{[1
]}

Zhang Z. ^{[1
]}

Zhao G. ^{[1
]}

Liu S. ^{[1
]}

机构：

[1] School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan

来源：

Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | 2024年 / 32卷 / 01期

关键词：

boosting tree; non-line of sight; Sage-Husa Kalman filter; UWB/IMU combined positioning;

D O I：

10.13695/j.cnki.12-1222/o3.2024.01.005

中图分类号：

学科分类号：

摘要：

In view of the problem of non-line of sight (NLOS) and random error in ultra-wide band (UWB) wireless positioning system in complex environment, a UWB/IMU combined positioning algorithm based on improved Sage-Husa Kalman filter (SHKF) is proposed. First, a boosting tree based on probability density is designed, and the NLOS signals is identified by introducing the probability distribution density of UWB/IMU collected feature data into the loss function of the boosting tree. Then, an improved SHKF algorithm is designed to define an adaptive factor according to the changing trend of innovation, and adjust the strategy of correcting the error of innovation in real time to adjust the influence of historical noise on the current positioning, so as to improve the stability and accuracy of UWB/IMU combined positioning. The experimental results show that the NLOS signal identification accuracy of the proposed method is up to 99.12%, and the root mean square error of positioning is reduced to 4.30 cm, which improves the positioning accuracy of UWB/IMU integrated system in complex environment. © 2024 Editorial Department of Journal of Chinese Inertial Technology. All rights reserved.

引用

页码：34 / 41

页数：7

共 16 条

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