Particle Swarm Optimization in SAR-Based Method Enabling Real-Time 3D Positioning of UHF-RFID Tags

Abstract

This paper presents a particle swarm optimization (PSO) in synthetic aperture radar (SAR) methods to enable real-time 3D localization of UHF-RFID tags. The reader antennas are moved through a moving agent (e.g., unmanned aerial vehicle, unmanned ground vehicle, robot) and they collect several phase samples by resembling a synthetic array. Thanks to the PSO approach the 3D matching function of the SAR method can be calculated in a reduced number of points by keeping an acceptable localization error. A numerical analysis demonstrates the method applicability through a comparison with conventional SAR methods based on the exhaustive search (3D dense grid) of the maximum point. Localization performance is investigated when an agent is equipped with a single antenna moving along a 3D trajectory or with two reader antennas at different height running a planar trajectory. Then, an experimental campaign in indoor scenario with an RFID-equipped unmanned ground vehicle shows the method effectiveness in performing real-time 3D positioning with centimeter-order localization error.