Research On Underwater Target Threat Assessment Based On Bayesian Network

Underwater battlefield threat assessment is of great importance to national maritime security.The environment of underwater battlefield is complex and changeable,and the underwater combat units can hide their traces easily so it is difficult to detect these units.These factors make the threat from underwater battlefield difficult to predict.In order to improve the combat capability and the capability of situation awareness of underwater battlefield,enhance the early warning ability of enemy units,speed up the defensive counter-response speed of our combat units,and provide decision analysis support for combat commanders,this paper uses Bayesian network theory to study the threat assessment method of underwater battlefield.This paper,combined with Bayesian network-related theory,puts forward an underwater battlefield threat assessment method based on Bayesian network,analyzes the threat factors of underwater battlefield and combat units,models the underwater battlefield threat factors with Bayesian network,builds an underwater threat assessment model based on Bayesian network;analyzes and improves Belief Propagation algorithm,put forward a new underwater battlefield threat assessment algorithm based on Bayeisan network.The proposed algorithm has been tested by simulation,and compared with TOPSIS method,AHP method and Elman neural network method.The validity of the model and algorithm is also verified.