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.