An Adjustment Algorithm for Multiple UAVs Based on Local Averaging

As the unmanned aerial vehicle system plays an increasingly important role in modern society, the problem of UAV formation adjustment has also attracted more and more scholars' attention. Passive azimuth-only positioning technology can reduce the electromagnetic radiation required for positioning, but it also brings great challenges to positioning. Taking the circular formation as an example, this paper discusses the passive triangulation model of pure azimuth angle, and proposes an optimization strategy based on local averaging, which can effectively solve the formation adjustment problem when there are position errors of multiple measuring points. In this strategy, the UAV under positioning is localized by three measurement groups at a time, and the UAV iteratively adjusts its position with a local average polar coordinate. Simulation experiments show that the strategy can effectively realize the autonomous coordination and coordination of multiple UAV formations, which has certain theoretical and practical significance.