Validation of Missile Simulation Model Based on Bayesian Theory with Extreme Small Sample

The cost of weapons and equipment, such as high-precision guided missiles, is high to manufacture, and the cost of live-fire launch test is also high. So the number of test data samples is very small, which cannot meet the sample capacity requirements of classic statistical methods. Therefore, this paper proposes a Bayes parameter estimation method based on Grey prediction Model and Bootstrap method (GM-Bootstrap), and it is applied to the simulation model validation under extreme small sample test. First, the Grey prediction Model (GM) is used to expand the extreme small sample, then the Bayes Bootstrap method is used to obtain the parameter distribution, and then the Bayes parameter estimation method is used to obtain the estimation of the unknown parameter. Finally, the simulation model validation under the extreme small sample test was completed through hypothesis testing. The credibility of the method is verified through an example, and a new method is provided for the costly validation of weapon equipment models.