UAV-Based Dynamic Object Tracking with Radio Map

Acting as dynamic base stations, unmanned aerial vehicles have a significant advantage over conventional base stations for dynamic object localization and tracking. In practice, however, the localization and tracking performance highly depends on the observation sequence of time-variant received signal strength (RSS) on UAVs from the dynamic object, which can be severely distorted by complex land layouts. In this paper, we propose dynamic object tracking by UAV with radio map, which contains abundant time-variant RSS knowledge. We generate time-varying radio maps from complex real-world topographic data. Then, we derive the grid-based method for dynamic object position estimation with the non-memoryless observations from the dynamic object. Numerical results show that the proposed algorithm can considerably improve tracking precision and efficiency for real-world topographical data.