Due to the increasingly prominent threat posed by unmanned aerial vehicle(UAV)swarm operations to key areas and targets,research on situation awareness response strategy for anti UAV swarm has been carried out.Firstly,the application scenarios of multiple early warning detection methods such as radar,radio,and optoelectronics are analyzed,and a joint multi-domain detection mode for countering UAV swarm is proposed,which combines long-range and short-range detection,high-altitude and low-altitude detection,and echelon deployment.Then,a hierarchical multi-source information fusion structure is constructed.In terms of target tracking,the tracking situation of group targets is classified,and the principles and characteristics of group detection,separation/merging detection,group expansion shape estimation,correlation and filtering algorithms in dense group target tracking are mainly explained.In terms of intention recognition,a hierarchical Bayesian Network based method for group intention recognition is proposed,and a multi-level group intention recognition model is established.The reasoning relationship between behavioral characteristics and target intentions is analyzed.The proposed situation awareness coping strategy can provide certain reference value for the design of countermeasures against UAV swarm.
维普
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