Abstract:

The angle of attack (AOA) is an important state parameter of flight. It is also a necessary parameter in flight control and navigation systems. The modern fighters have increasing demands on the AOA accuracy. The performance of air data systems (ADS) seriously declines under transonic conditions. The accuracy of ADS-AOA is seriously affected. In view of air data sensor configuration features of testing plane, a transonic ADS-INS AOA two-step fusion algorithm based on variable parameters complementary filter and neural network is designed in this paper to achieve fusion of INS and ADS. The divergent transonic INS vertical velocity is resolved. Variable parameters complementary filter and neural network are used to fuse and correct ADS-INS AOA. The result approaches the true AOA with stability and reliability. Actual flight data are used to validate the two-step fusion algorithm. The results show that the AOA after fusion and correction can eliminate violent fluctuations of ADS-AOA under transonic condition. Its tendency coincides with the true AOA with small error.

Key words: air data systems,, INS, angle of attack, complementary filter, BP neural network, fusion algorithm