Nonlinear model of the unmanned coaxial helicopter system was built

and on account of considering its strong nonlinear character

as well as the aerodynamic parameters were variable under different flight modes

the unscented Kalman filter (UKF) was introduced to solve the nonlinear model identification problem of coaxial helicopter. It did not only avoid the limitations that linear model was only appropriate to hover modes of helicopter model

but also provided the basis for the online adaptive control of helicopter system

in which autonomous unmanned coaxial helicopter's full envelope flight could be possible. Identification of the FH-1 unmanned coaxial helicopter developed by Beijing University of Aeronautics and Astronautics was simulated by the approach and the predictive error method(PEM). Simulation experiment results show that the online identification of coaxial helicopter nonlinear system based on UKF does not depend on the selection of initial parameters

parameters can converge within the validity period of 10s

and the accuracy of identification reached 80%

which is higher than the classical PEM

so it has a certain practicality.