Adaptability Assessment For The Hit Accuracy Of Integrated Guidance Weapon Systems

The precision analysis and evaluation is the key to improve the performance of integrated guidance weapon system.And the standard tests can not be carried out as a result of many restrictions existing in the testing procedures.Thus a large amount of equivalent tests are designed and used to assist identification and finalizing of weapons.But the data of equivalent tests can not be used to assess the performance of weapons in the standard environments.This paper focus on establishing a complete conversion frame of equivalent tests,and presenting methods for adaptability assessment of integrated guidance.The main contents and innovation points of this paper are as follows:1.The mathematical description for the error of integrated guidance weapon system,and the whole conversion frame and adaptability assessment of equivalent tests for integrated guidance are presented based on the theory and methodology of UQ.The error sources of SINS are researched detailedly.The integrated error response model of SINS/SMNS is presented based on non-equidistance Kalman filtering,and the equivalent conversion of the system is researched by simulation.2.An novel optimization method for choosing the priori sample size in the Bayesian analysis is presented.The conclusion is proved that the novel method here,in the case there existing systematic difference or the distortion of prior information,is superior to the posterior-weighted Bayesian estimation method with information credibility in much possibility,moreover much better than traditional Bayesian method.Moreover,taking the estimation of the dispersion parameters of the normal distribution for example,a posteriorweighted Bayesian estimation method considering the credibility of the prior information was given.Both theoretical analysis and simulation results show that our method is credible and it is better than classical Bayesian method.3.A weighted method considering the credibility of the prior information is proposed for Bayesian estimation algorithm and the weighted estimation of normal distribution parameters is provided.And the statistical diversity between the weighted and classical methods is quantified,and upper bound of the calculation errors caused by prior distortion is deduced for mixture of finite normal distributions.Taking the estimation of the dispersion of the guided weapon impact points as an example,the conclusion is drawn that our method is credible.