信息熵在潜艇作战系统多目标任务调度中的应用

Application of Information Entropy Theory to Analyzing Tasks Scheduling for Submarine Combat System

为解决潜艇多目标作战的任务调度问题,针对处理器服务的作战任务队列,提出了基于目标信息增量的作战任务调度算法。运用信息处理系统计算各目标信息增量来描述作战系统对各目标状态的了解程度,并分别给出了作战系统目标探测、识别和跟踪过程中信息增量的计算方法。仿真结果表明,该方法能够定量描述作战任务调度和目标信息不确定性之间的关系,具有一定的可行性和实用性。

A method for multi-objective tasks scheduling based on information gain was pro- posed. In order to describing the understanding of target state for combat system, informa- tion gain of every target was calculated. The information entropy was used to describe the uncertainty of target information. On the basis of which, the information gain in the detec- tion recognition, and tracek state was carefully analyzed. The capability that the extended kalman filter could estimate the state of target was used to analyze the underwater bearings- only passive target motion. The results of simulation show that the information entropy could quantificationally describe the combat tasks scheduling, and the method is feasible and practical.