基于多源信息融合的装备作战试验评估OA北大核心CSTPCD

The use of modeling and simulation methods in equipment test process can reduce the dependency on physical on-site test,while conducting some experiments that are difficult to achieve in physical on-site test can be done.Therefore,the evaluation of combat tests includes not only simulation data,but also the actual setting-up data and various sources and types of data.The suitable methods need to be selected for analyzing and processing the experimental data.The data are classified according to their characteristics,different pre-processing methods for different types of data are utilized.The fusion results of the large sample frequency method and the small sample Bayesian method results are respec-tively regarded as prior information and observation sample data.The Bayesian method is used to update the prior information parameters,and the obtained result is the multi-source data fusion result.Based on evaluation indicators and fusion results,the corresponding evaluation models are utilized to predict and evaluate the potential combat effectiveness and operational suitability of equipment.