新型飞行器对气动特性的预示精准度提出了更高的要求，为此研究了一种适用于多条飞行试验数据的气动特性修正框架，实现了对地面气动模型及先验不确定性模型的修正。基于试验数据特点，首先从模型辨识角度，改进了传统的多元正交函数法，构建了多试验数据模型项的统计优选准则，设计了基于总体最小二乘思想的定制化参数估计算法；然后从不确定度量化角度，估计出了气动修正模型的总偏差，校验了先验不确定性模型。最后应用提出的修正框架处理某飞行器的10条试验数据。结果表明相比于原始地面气动特性预示方式，修正后的方式，一方面预测的气动系数更接近测量的气动系数，另一方面估计的气动误差带具有较少的误差带外测量点及最高的精细程度。
The novel aircraft has higher requirements for prediction accuracy of aerodynamic characteristics. Therefore, this paper studies an aerodynamic characteristics correction framework for multiple flight test data to achieve correction of ground aerodynamic model and prior uncertainty model. Firstly, to improve the accuracy of model identification, the traditional multivariate orthogonal function method is improved based on the characteristics of experimental data. Statistical selection criteria for multi-test data model items are constructed, and the customized parameter estimation algorithm is designed based on the total least square method. Then, for the purpose of uncertainty quantification, the total deviation of the aerodynamic correction model is estimated, and the prior uncertainty model is corrected. Finally, the proposed correction framework is used to process 10 test data of a certain aircraft. The results show that compared with the original ground aerodynamic characteristics prediction method, the revised method can yield more accurate prediction of aerodynamic coefficients, and fewer out-of-band measurement points and higher accuracy in estimation of aerodynamic error bands.
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