Source Localization Based on UAV Swarm Trajectory Optimization with Incomplete Measurements
Pengwu Wan, Yifan Wen, Shujie Hu, Chenehen Duan, Ze Zhang · 2024
In complex urban environment, the source localization is hindered as sensors cannot simultaneously receive signals due to building occlusion, the phenomenon known as incomplete measurements, which could adversely affect the localization per-formance. In order to improve the accuracy of source localization, a technique based on the DAV swarm trajectory optimization is exploited in this paper. Firstly, the received signal strength (RSS) is utilized to obtain the rough estimation of the source to adjust the trajectory of UAV s. Secondly, by optimizing the UAV flight path, time difference of arrival (TDOA) and Doppler frequency shift (DFS) are employed to localize the source. Then, the non-convex problem is established by maximum likelihood (ML) and modified to the semi-definite relaxation (SDR). Finally, the source localization is obtained by solving the convex optimization problem. The proposed methods achieve superior performance over the existlng methods. as validated by using simulation.