This paper presents an adaptive information fusion method to improve the

accuracy and reliability of the altitude measurement information for small unmanned aerial

rotorcraft during the landing process. Focusing on the low measurement performance of

sensors mounted on small unmanned aerial rotorcraft, a wavelet filter is applied as a

pre-filter to attenuate the high frequency noises in the sensor output. Furthermore, to

improve altitude information, an adaptive extended Kalman filter based on a maximum a

posteriori criterion is proposed to estimate measurement noise covariance matrix in real

time. Finally, the effectiveness of the proposed method is proved by static tests, hovering

flight and autonomous landing flight tests.