A Resetting Approach for INS and UWB Sensor Fusion Using Particle Filter for Pedestrian Tracking

Abstract

Sensor fusion of inertial navigation system (INS) and ultrawideband (UWB) technology is an effective approach to enhance the accuracy and robustness of indoor pedestrian tracking system. The main drawbacks of state-of-the-art approaches are the number of required UWB anchors and poor system scalability in terms of cost-effectiveness when covering a large indoor area. In this article, an INS and UWB fusion system using particle filter (PF) for pedestrian tracking is proposed. The system utilizes only distance measurements from UWB anchors and incorporates a particle resetting approach. The resetting approach aims to address the lost track problem in PF, which limits the long-term reliability of PF-based fusion tracking systems. The developed pedestrian tracking system is able to provide accurate and long-term robust tracking performance, and at the same time, possesses high scalability to cover a large area of indoor environment using sparsely deployed UWB anchors. A practical experiment is conducted with test path length over 500 m to demonstrate the effectiveness of the proposed approach, which is able to reduce the mean position error by 39.42% when compared to INS only result.