UAV trajectory planning and tracking for user localization in wireless networks

In this paper, we study UAV-aided user localization in wireless networks without assuming perfect knowledge of the UAV position. The problem is therefore formulated as joint user localization and UAV tracking. We exploit time-of-arrival (ToA) and received signal strength (RSS) measurements collected by a UAV and propose an Expectation–Maximization-based least-squares simultaneous localization and mapping (SLAM) framework to classify measurements as line-of-sight or non-line-of-sight, learn the radio channel, and jointly localize users and track the UAV. The framework incorporates auxiliary measurements from onboard GPS and inertial measurement unit (IMU) sensors to improve accuracy. In addition, UAV trajectory optimization is performed to further enhance localization performance. Simulation results demonstrate superior performance compared to existing approaches.