Diffusion Target Tracking Based on Software-Defined Multi-UAV Network: A Cooperative Autonomous Clustering Approach

Abstract

This paper is centered on enhancing the efficiency of collaborative tracking and minimizing energy consumption within the framework of multi-Unmanned Aerial Vehicle (UAV) collaborative tracking, particularly for diffusion targets. This paper utilizes the software-defined networking (SDN) technique and proposes the concept of UAV-based SDN-enabled Wireless Network (SDWN). In order to collaboratively track the diffusion target in a fixed environmental field, this paper, grounded in the artificial potential field theory, puts forward a multi-UAV collaborative tracking strategy with autonomous clustering capabilities. Under the governance of the proposed strategy, the UAV-based SDWN initially tracks the target environmental field values by means of a proposed inverse-distance-weighting method. Subsequently, once the UAV-based SDWN reaches the target environmental field values, a contour tracking algorithm based on multi-UAV autonomous clustering is utilized to yield the collaborative tracking of the environmental field. Simulation results reveal that the proposed approach can precisely detect target contours. Moreover, the proposed method shows great potential in practical complex scenarios, e.g., the scenarios with multiple diffusion sources.