Adaptive swarm optimization for locating and tracking multiple targets

Locating and tracking multiple targets in the dynamic and uncertain environment is a crucial and challenging problem in many practical applications. The main task of this paper is to investigate three fundamental problems, which are composed of the identification of irregular target, locating multiple targets and tracking multiple targets. Firstly, the proposed objective function successfully gets the target's shape to discern eccentric target in the specific environment. Secondly, for the sake of locating multiple targets, the adaptive PSO algorithm divides the swarm into many subgroups, and adaptively adjusts the number of particles in each subgroup by the competition and cooperation technology. Thirdly, in order to track multiple targets in the dynamic environment, the proposed swarm optimization has the characteristic of the adaptively covered radius of the subgroup according to the minimum distance among other subgroups. To show the efficiency and high performance of the proposed algorithms, several algorithms chiefly concentrate on locating and tracking three ants in the practical systems.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Cost function enlarges adjacency region of the target and smooth the landscape. ► Adaptive PSO algorithm introduces the cooperative and competitive mechanism. ► Swarm optimization adaptively adjusts the covered radius of each subgroup. ► The experiment concentrates on ant identification with different directions. ► Results are probably helpful for self protection in the dangerous environment.