Research On Algorithm Of Ship Missile-Defense System Decision Model Based On Bayesian Networks

Due to the appearance of anti-ship missiles (ASMs) throughout the world, they have brought naval ships tremendous threats. New threats bring new challenges, Ship Self-Defense System (SSDS) begins to appear on the war scene, and becomes absolutely necessary "amulet" of naval ships.However, because of high speeds and the low trajectories of modern ASMs the reaction times are reduced. With so many uncertain factors and informations in war situation, modern war environments are being more and more complicated, the decision-making process may be very complex for Ship Self-Defense System sometimes.The even more difficult thing is, there are interactions and physical constraints between multiple weapons systems, we can't always allocat the self defense weapon resources in optimum way.Bayesian Network (BN) is one of the most effective theoretical models for uncertainty knowledge expression and reasoning. It can be applied to decision with various dependent factors. BN is a directed acyclic graph with network structure, which is intuitionistic and easy understanding. It can handle multi-information expression, data fusion and bi-directional parallel reasoning. The ability to colligate the prior information and the current information makes the inference much more accurate and believable. So it is a better choice to use BN for dealling with uncertainties caused by environmental conditions and sensor measurement errors. Under the background of single-ship missiles defense system, the paper studies the threat assessment method based on Bayesian Network. The theoretic basis of the BN is introduced firstly. According to several problems considered in threat assessment, there are basically two components in this process: intent assessment and capability assessment. The Bayesian Network models of threat identification, intent assessment, capability assessment and threat assessment are constructed. And then Tabu search algorithm recommended to solve the weapon-target assignment problem is discussed. Simulation results demonstrating feasibility of the approach presented.