Air data assisted attitude algorithm based on fuzzy adaptive Kalman filter

Aimed at solving problems that accelerometers cannot be utilized in maneuvering carriers to modify its horizontal attitude and that noise statistical properties change with the actual working conditions in low accuracy attitude and heading reference system (AHRS), an air data assisted attitude calculating method based on fuzzy adaptive Kalman filter is proposed. Firstly, for assisting horizontal attitude calculation, an attitude algorithm is presented to make use of air data, such as true airspeed, angle of attack and sideslip angle information to compensate maneuvering acceleration, combining the advantages of both air data system and AHRS. Secondly, estimating and modifying parameters of the observer model and system characteristics is processed based on fuzzy adaptive Kalman filter in order to realize optimal estimation of horizontal attitude. Finally, simulation of flight test data from a type aircraft flight is conducted. Simulation results demonstrate that the accuracy of attitude angels reaches 1.3 °, and it plays a significant role in correcting large deviations. Thus, to non-compensated maneuvering acceleration algorithm and conventional Kalman filter, this method is superior in attitude estimation and has practical value.