Multi-target Coverage for UAV Swarms Using Density Clustering with Quadratic Perturbation Strategy.

Aiming at the problem of high cost-effectiveness ratio and redundant resource, a new multi-target coverage algorithm for UAV swarms communication coverage is proposed in this study. Firstly, the proposed algorithm takes each target point as the center and the distance of a single UAV communication coverage as the radius. Then, the number of target points in each circle is calculated and the circle with the maximum number is retained. Finally, using means centering and quadratic perturbation, the target points and circle center within this circle are redetermined. For the uncovered target points, the above operations are repeated until all target points are covered or the number of clusters are more than the UAVs. The experiment results show that the proposed algorithm achieves a coverage of nearly 90% random target points, which is 16% higher than conventional algorithms. Therefore, the proposed algorithm is well applied to cooperative communication support and target area coverage in the combat.