Use of particle filtering in received signal strength indicatior based localization by drone base stations

Drone Base Stations (DBSs) provide flexible deployment and line-of-sight coverage opportunities, which led to many use cases, such as broadband Internet, military, surveillance, agriculture etc. DBSs can optimize and adapt their positions based on user location information. Especially in GPS-denied tactical scenarios ground user location estimation is an important problem. In this work we investigate particle filter as a method of user position estimation. We utilize the recently proposed air to ground pathloss model for RSSI-based location estimation. We investigate different DBS trajectories and various resampling methods. Also, we investigate the tracking performance of the filter by comparing different simulation results including the total energy needed by DBS to track one target.