In order to further bring the comprehensive effect of multiple sensors into play,and to enhance the utilization rate of resources,and to maximize the demand for detection and tracking of mul-tiple targets,a multi-sensor adaptive scheduling method is proposed to address the such issues of tra-ditional multi-sensor scheduling methods as ignoring dynamic environmental changes,considering only a single task,and weak algorithm performance,etc.This method analyzes and designs the multi-sensor scheduling model,establishes a sensor efficiency function by combining three indicators:task priority,target threat degree,and detection and tracking benefits,and uses this as an adaptive objective func-tion.The flower pollination(FP)algorithm is improved by introducing a new local pollination operator,modifying the global pollination process,and designing a dynamic switching probability,and is applied to the optimization solution process.Finally,the simulation experiments show that this method can adaptively schedule multiple sensors according to environmental changes and task requirements and can significantly improve the resource utilization rate of multiple sensors.
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