The Rescuer’s Navigation in Metro Stations Based on Inertial Sensors and WiFi

The demand for metro station rescue navigation is increasing. This paper presents an improved particle filter to challenge the navigation problem in metro stations. A particle filter is often used to estimate the position of pedestrians. However, the particle-impoverishment problem is inevitable. To solve this problem, a dingo optimization algorithm (DOA) with global search ability is introduced, and an improved particle filter called a dingo particle filter (DPF) is proposed. Dead reckoning (DR) is taken as the system equation, and WiFi matching results are used as the observation equation. The improved particle filter algorithm introduces a dingo optimization algorithm to improve the diversity of particles and effectively reduce the particle-impoverishment problem. The experimental results show that the average positioning accuracy is 1.1 m and 1.2 m.