效能评估ADC模型中可信赖度矩阵算法探讨

ADC模型是目前评价复杂武器系统效能的标准方法,在实践中得到了广泛应用.但多数应用中可信赖度矩阵计算过于简化,致使效能评估结果误差较大.为了提高模型的有效性和可信度,将武器系统在执行任务后任意时刻处于某种状态看作是一个随机过程,应用连续时间齐次马尔可夫链的柯尔莫哥洛夫向前和向后方程建立可信赖度矩阵计算模型,求解矩阵微分方程得到转移概率.最后,以某型近程地空导弹武器系统效能评估为应用背景,给出了应用案例,验证了模型的有效性,并提出了进一步研究的方向.

Arithmetic of dependability matrixes in the ADC effectiveness evaluation model

At present,the ADC model is a standard method used to evaluate the complex weapon system effectiveness and has been widely applied in practice.But in most applications,the compution of the dependability matrix is unduly simplified,so that a larger error is caused in effectiveness evaluation result.In order to improve the validity and reliability of the model,the random state of weapon systems after accomplishing the mission at random time is regarded as a random process,and the computing model of the dependability matrix is established by using Kolmogorov backward and forward equations of the continuous time homogeneous Markov chain.The transfer probability is found by solving the matix differential eguation.Finally,an application case example which is based on a short range ground-to-air missile weapon system effectiveness eavaluation validates the model and the future research orientation is put forward.