Method of small unmanned aerial rotorcraft altitude information fusion based on wavelet filter

Focusing on the low performance of the sensors for the small unmanned aerial rotorcraft, an adaptive Kalman method based on filter data was proposed to improve the accuracy and reliability of the altitude measurement information. Using the wavelet decomposition and reconstruction filter, the high frequency noise of altitude information for the small unmanned aerial rotorcraft was eliminated. Furthermore, since the global positioning system (GPS) measurement accuracy was influenced by GPS satellite-number fluctuation, an adaptive Kalman filter was used to improve altitude measurement performance. At last, hovering flight and three-dimensional track flight test were used to verify the feasibility and effectiveness of the method.