Bayesian estimation of missile hit accuracy for Dirichlet distribution

Based on the differential impact of the spatial distribution of impact points on target damage effectiveness, the probability distribution model of missile hitting different important areas of target was constructed to realize expansion of the traditional hit accuracy concept. Aimed at the reality of actual missile hitting targets with complex process, high cost and low frequency, Bayesian method was used to fuse multi-source information, and missile hit accuracy was estimated on the basis of the idea of region division, distribution determination, prior fusion and posterior solution. The Dirichlet distribution was selected as the prior distribution of hit accuracy parameters, the D-S (Dempster-Shafer) evidence theory was used to fuse the prior information and the posterior distribution of accuracy parameters was solved by MCMC (Markov chain Monte Carlo) method. Example results show that this method can describe the probability of missile hitting different important areas of the target in detail, and scientifically integrate multiple types of prior information about hit accuracy, which provides theoretical references for missile hit accuracy estimation methods and test schemes optimization.