Set-membership method improves locating intermittent rf sources by uavs
Set-membership localization of intermittent RF sources using a fleet of collaborating UAVs
Multiagent Systems
Summary
Tracking where radio signals come from can be tricky when the signals turn on and off at unknown times. The paper presents a new way to estimate where these signals originate using groups of drones that work together. This method narrows down possible source locations more quickly and accurately than traditional statistical approaches. The authors tested it with simulations and found better results than a standard Bayesian method.
What this means in practice
- •For drone fleet operators: Use drone teams with the presented method to locate intermittent RF devices in complex environments more quickly and accurately.
- •For wireless network engineers: Improve detection and localization of intermittent radio transmitters causing interference using collaborative UAV observations and set-membership estimation.
Authors
Jacques Bois, Raul de Lacerda, Michel Kieffer
Abstract
This paper proposes a set-membership approach (SMA) to localize radio frequency (RF) sources observed by a collaborating fleet of Unmanned Aerial Vehicles (UAVs). Considering frequency-separable RF transmitters with intermittent and periodic emission patterns, %and unknown but bounded periods the SMA evaluates set estimates of the source locations and a set free of sources. Simulation results show that SMA outperforms a Bayesian baseline approach in terms of localization accuracy and convergence speed.