Radar Tracking and Identification of Biobimetic UAV Cluster Targets

Abstract

The rise of biomimetic unmanned aerial vehicle (UAV) cluster has brought new challenges for radar target tracking and identification. Different cluster flight modes will have different impacts on radar data processing and cluster target identification. For analyzing the influence mechanism of the cluster on radar tracking and identification, this paper models the flight process of UAV cluster based on three kinds of species: geese, wolves and bees, which respectively simulated the large-scale transport, close-in rounding attack and robust information communication of UAV cluster. Secondly, it discusses the influence mechanism of different cluster modes on several algorithms of tracking: track initiation, data association and tracking filter. Finally, combined with the characteristics of three biological movements, it designs the identification methods of cluster event pattern based on clustering in detail, and gives the judgment rules. The simulation results show that there is the suitable combination of radar data processing algorithms for different clustering modes. The optimized tracking algorithm combination based on different clustering modes can effectively improve the tracking accuracy of the radar cluster target, and can reduce the time cost. Moreover, the method proposed in this paper can realize the identification of different cluster patterns to the judgment of target intention and provide the subsequent processing.

Keywords

• |biomimetic group|uav cluster|geese|wolves|bees|radar target tracking