基于改进灰色关联分析的仿真模型综合验证方法

灰色关联分析是仿真模型验证最有效的方法之一,但基于常规灰色关联分析进行仿真模型验证时存在着未考虑数据序列数值间的接近程度、给出的处理1组飞行试验序列与1组仿真实验序列的灰色关联度与靶场实际问题不符、无法获得模型的整体性能评价等问题,会引起决策风险较大。为此,提出一种基于改进灰色关联分析的仿真模型综合验证的方法。在灰色关联系数的计算中引入数据距离,从而使灰色关联度的计算值综合了时间序列几何形状的相似性和数值距离的接近性两个属性,提高了仿真模型验证的准确性。通过概率和计算能够处理1组飞行试验数据和多组仿真实验数据的关联分析问题,从而融合了试验过程的随机因素,在小样本飞行试验条件下充分利用了仿真实验信息,提高了仿真模型验证的可靠度。对不同的实际飞行试验样本赋予不同的重要性权重,从而得到仿真模型的整体性能评估。同时给出具体的基于改进灰色关联分析模型综合验证的操作过程,并证明改进灰色关联度模型满足灰色关联定理及相关性质。通过实例分析验证了该方法的合理性和有效性。

Research on Comprehensive Validation of Simulation Models Based on Improved Grey Relational Analysis

Grey relational analysis (GRA) is usually used to validate the simulation models because of its advantage in the field of time series relational analysis. The ordinary GRA stresses the similarity but ignores the proximity between two test time series while the proximity is part of model error. The grey relational degree given by a set of flight test sequences and a set of simulation test sequences is inconsistent with the practical problems of firing range. The ordinary GRA cannot be used in the overall performance evaluation of simulation model, which leads to a high risk of decision-making. An improved grey relational analysis is proposed to reduce the risk, in which the similarity and the proximity between the simulation test time series and the flight test time series are considered. At the same time it can analyze the time series which has not only one dimension but also more than one dimension by calculating probability sum, and so it fuses random factor of random process and makes full use of simulation test data with small sample flying test. Besides the new grey relational analysis improves the performance of GRA and has higher precision and reliability for the validation of simulation models. The proposed model can be used to solve the relational analysis problem with many characteristics of behavior, and the operational steps are listed in detail. Data test and case study are given to show the reasonability and validity of the improved method.