Strong Tracking Particle Filter Based on the Chi-Square Test for Indoor燩ositioning

Abstract

In recent years, a number of wireless indoor positioning (WIP), such as Bluetooth, Wi-Fi, and Ultra-Wideband (UWB) technologies, are emerging. However, the indoor environment is complex and changeable. Walls, pillars, and even pedestrians may block wireless signals and produce non-line-of-sight (NLOS) deviations, resulting in decreased positioning accuracy and the inability to provide people with real-time continuous indoor positioning. This work proposed a strong tracking particle filter based on the chi-square test (SPFC) for indoor positioning. SPFC can fuse indoor wireless signals and the information of the inertial sensing unit (IMU) in the smartphone and detect the NLOS deviation through the chi-square test to avoid the influence of the NLOS deviation on the final positioning result. Simulation experiment results show that the proposed SPFC can reduce the positioning error by 15.1% and 12.3% compared with existing fusion positioning systems in the LOS and NLOS environment.