Application of information entropy theory to analyzing tasks scheduling for submarine combat system

A method for multi-objective tasks scheduling based on information gain was proposed. In order to describing the understanding of target state for combat system, information 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 detection 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.