Pedestrian Dead Reckoning and WIFI Fusion Positioning Based on Chaotic Particle Swarm Optimization

Inertial navigation is an autonomous navigation without the help of external force (receiving signals outside the body), which can provide continuous real-time position, speed, attitude information, and has the characteristics of high short-term accuracy and strong anti-interference ability. Pedestrian Dead Reckoning (PDR) is a positioning technology widely used in mobile devices, using an inertial measurement unit to measure and count the number of steps, step length and direction walked by walkers, and to calculate the walking trajectory and position of walkers. However, the inertial sensors built into many mobile devices are not highly accurate, and the limbs may shake irregularly during walking, resulting in PDR positioning errors that accumulate over time. We develop a WIFI localization algorithm to assist PDR positioning, and propose the Kalman filter algorithm optimized by chaotic particle swarm optimization for fusion localization. Experimental results show that the fusion algorithm has achieved higher accuracy and more robust indoor positioning.