Vehicle Tracking Using Particle Filter in Wi-Fi Network

Abstract

Location tracking for vehicle plays a key role in increasing road safety and transportation efficiency. In this paper, a Wi-Fi based real-time tracking system which can work in both indoor and outdoor environments is presented. The proposed system estimates the location of vehicle using the Received Signal Strength (RSS) fingerprints of transmitted Wi-Fi Access Points (APs) and Particle Filter (PF). A simple, effective approach based on Inverse Distance Weighting (IDW) is designed to build fingerprints database effectively. Outdoor experiments have been carried out to investigate the usefulness of IDW and PF. Experiment results show that a tracking system based on Wi-Fi signals is able to give a position estimate of moving vehicle in real time, and that it can be significantly enhanced by PF compared with by Kalman Filter (KF).