WBF-PS: WiGig Beam Fingerprinting for UAV Positioning System in GPS-denied Environments

Abstract

Unmanned aerial vehicles (UAVs) are being investigated to substitute for labor in many indoor applications, e.g., asset tracking and surveillance, where the global positioning system (GPS) is not available. Also, emerging autonomous UAVs are expected to land in indoor parking aprons automatically. Such GPS-denied environments require alternative non-GPS positioning methods. Although there have been some vision-based solutions for UAVs, they perform poorly in the scenes with bad illumination conditions or estimate only relative locations but not global positions. Other common indoor localization methods do not cover UAV factors, such as low power and flying behaviors. To this end, we propose a practical non-GPS positioning system for UAVs, named WBF-PS (WiGig Beam Fingerprinting based Positioning System), using low-power, off-the-shelf WiGig devices. We formulate a 3-dimensional beam fingerprint for the positioning by leveraging the diversity of available transmitter/receiver beams and the link quality. To augment the positioning accuracy, we not only use a weighted k-nearest neighbors algorithm to overcome partial fingerprint inaccuracy but also apply the particle filtering technique into considering the UAV motion. We prototype and evaluate WBF-PS on a UAV platform. The result shows that the positioning errors at the 90th percentile are below 1 m in various cases.