Noise rejection and anti-divergence of key sensors in a flight control system based on Adaptive Fading EKF

There are two important problems in autopilot of UAV. The first one is attitude divergence and the second one is inaccuracy of velocity, attack angle and sideslip angle sensors. Conventional extended Kalman filter will be diverge in this situation due to the error of low cost sensors. This paper cope with these problems via adaptive fading extend Kalman filter (AFEKF) with innovative modeling of UAV, which fuses sensors information of Inertial Navigation System (INS), Air Data System (ADS) and Global Navigation Satellite System (GNSS) and realizes noise rejection of velocity, attack angle and sideslip angle sensors and anti-divergence of attitude.

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