Influence of refractive index accurate model of supersonic vehicle window flow field on aero-optical characteristics

Abstract

Aircraft with a supersonic speed has a complex flow field around its optical window. The precise modeling of the refractive index of the flow field is of great significance for the research of optical homing, laser guided and optical remote sensing. However, in practice, It difficult to obtain a refined refractive index model because of the sparse sampling points distribution near the optical window. The density flow field was converted into the refractive index field using the Gladstone-Dale relation. The obtained refractive index field data was inputted into the back propagation neural network to find the refractive index field distributions with different degrees of refinement. The results of aero-optical effects of supersonic aircraft using back propagation neural network combined with ray tracing method show that: flight height and angle of incidence are important indicators that affect aero-optical effects. Meanwhile, the refined refractive index field has a very important effect on the parameters of aerodynamics such as imaging displacement, deflection angle, optical path difference. But there is little effect on the Strehl ratio. The use of back propagation neural network algorithm to accurately obtain the refractive index will greatly ensure the accuracy of aerodynamic optical results.