A Dynamic Window-Based UWB-Odometer Fusion Approach for Indoor Positioning

作者：Hui Zhang, Xidong Zhou, Hang Zhong, He Xie, Wei He, Xuan Tan, Yaonan Wang · 发表于：IEEE Sensors Journal · 年份：2022 · DOI：10.1109/jsen.2022.3228789 · 被引用次数：28 · 研究领域：Indoor and Outdoor Localization Technologies、Underwater Vehicles and Communication Systems、Target Tracking and Data Fusion in Sensor Networks

The positioning system based on ultrawideband (UWB) can achieve centimeter-level positioning accuracy, which is now widely used for indoor positioning. However, UWB is subject to multipath effects and nonline-of-sight (NLOS), which can cause positioning errors. And a UWB positioning system with a minimum of three anchors is costly and difficult to deploy, which is not an economical option. This article presents a low-cost UWB-odometer fusion method for mobile robot localization, which enables global localization using only one UWB anchor. To improve the positioning accuracy and eliminate the influence of cumulative odometer error, we propose a dynamic window-based particle filter (DWBPF). It solves the problem of particle convergence and track loss. It also adaptively modifies the score weights according to the power difference of the UWB to achieve a more robust and accurate positioning. The experimental result shows that the system has a high positioning accuracy of 0.061 m.