Research On The Multi-sensor Integrated Navigation System Of Multi-rotor UAV

Integrated navigation system is an important part in the multi-rotor Unmanned Aerial Vehicles(UAV), and is the foundation to realize a stable autonomous flight control. In this paper, a serial of researches were conducted on the key technology of multi-sensor integrated navigation system. These researches were based on an independently designed Unmanned Aerial Vehicles platform with a new structure of six axis and twelve rotors, and is supported by the National Natural Science Fund. A multi-sensor integrated navigation system was designed considering the dynamics theory of multi-rotor UAV, sensor calibration technology and information fusion technology. Some actual flight conditions such as the statistical properties of UAV’s noise, dynamic change in navigation information and the external environment disturbance were studied to ensure the accuracy and stability of the navigation. The effectiveness of this navigation system was verified through an actual trajectory tracking experiment of the UAV. This paper mainly includes the following aspects:(1) The Hex-Rotor aircraft’s dynamics characteristics were studied. Through some reasonable hypothesis and simplification, a mathematical model of UAV was established. The theory and method of information fusion technology in the multi-sensor integrated navigation system was studied. The hybrid data fusion structure of the integrated navigation system was determined by the unique dynamics of multi-rotor Unmanned Aerial Vehicles. In the meantime, the mechanical layout and navigation information decoding were completed.(2) The characteristics and error compensation of the main sensors were studied and a deterministic error and random error model were established. Through the ellipsoid fitting method, the deterministic errors of multiple sensors could be corrected at the same time. A Kalman filtering algorithm was applied in random error correction and was proved to be effective by experimental results. In the meantime, considering the uniqueness of the magnetometer error in UAVs, a special magnetometer calibration method was designed using the offline space least-square method to control the quantity change of compass. Accurate magnetometer data was acquired through calibration.(3) Research on integrated navigation information fusion technology was conducted and a mathematical model of information integration system was established. An information fusion structure was designed, and fusion algorithm was improved against the self-disturbance characteristics of the multi-rotor UAV. This system ensured the credibility of navigation information and met the requirements of UAV’s autonomous flight.(4) Research on attitude stabilization and trajectory tracking control method was conducted and an attitude stability control algorithm was studied to erase the influence of unexpected external disturbance from external environment. The effectiveness of the navigation system was verified through the actual trajectory tracking experiment, and an autonomous flight of the UAV was realized.At the end of the article, all the work that has been done and the main innovation points are summarized and future work that needs to be done is prospected.