潜射反舰导弹靶场试验先验信息融合方法仿真

摘要

How to acquire proper prior distribution is a key problem in submarine launched anti-ship missile range trial synthetical assessment based on the Bayes. When prior information comes from different sources,the rational and objective usages of the information is needed. In order to solve the problem,Bayes,DS and weighted fusion methods are presented to fuse prior information. Through simulation,the three fusion models are compared and their characters are analyzed,from the result some profitable engineering applying suggestions are given.%在基于Bayes理论的潜射反舰导弹靶场试验综合评定中，先验分布的获取和表示是一个关键问题，尤其在先验信息多源型的情况下，更需要合理客观地综合利用这些信息。针对此问题，建立了Bayes融合法、DS融合法和加权融合法等先验信息融合模型。通过仿真，比较分析了这3种方法的特点，并给出一些有益的工程应用建议。