基于Chebyshev-Taylor-Fourier混合级数模型函数的多源气动数据融合方法

针对飞行器气动力多源数据融合、飞行试验气动辨识问题，提出了一种基于Chebyshev-Taylor-Fourier混合级数模型函数、不确定度平衡权函数和加权最小二乘原理的多源数据融合和辨识方法.该方法采用二元Chebyshev级数、Taylor级数和Fourier级数技术建立飞行器气动模型函数，采用权函数技术平衡各数据源间的不同精度和不确定度，采用最小二乘法原理确定超定方程组解，从而获得Chebyshev-Taylor-Fourier混合级数模型函数的各项参数值，最终确定多源数据融合的飞行器气动力（力矩）系数模型函数数学表达式.典型的应用实例表明该方法高效实用、精度可靠，工程应用前景良好. 

A Fusion Method for Multi-Source Aerodynamic Data Based on Chebyshev-Taylor-Fourier Combined Series Model Function

A fusion method for multi-source aerodynamic data and an identification approach for air vehicles were proposed based on a Chebyshev-Taylor-Fourier combined series model function,an uncertainty balance weight function,and the least-squares principle.In this approach,an aerodynamic model function was established using a bivariate Chebyshev series,a multivariate Taylor series and a Fourier series.A balance between different accuracy and uncertainty was struck by employing some weight functions.Overdetermined equations were solved by using the least-squares principle.All parameters of the Chebyshev-Taylor-Fourier combined polynomials were acquired.Finally,the aerodynamic mathematic model expression of multi-source data fusion function for an air vehicle was determined.A typical application demonstrates that the method has high efficiency and practicality,reliable precision,and good prospect for engineering applications.