Real-time Estimation of Atmospheric Disturbance for Unmanned Helicopter based on Multi-source Navigation Data
Ke-cheng Sun, Qing-hua Zeng, Jian-ye Liu, Ya-jing Zhou, Yu-ting Dai, NRC, Nanjing University of Aeronautics and Astronautics (NUAA), China
Taking advantages of low cost and zero casualties, Unmanned Aerial Vehicle (UAV) is widely used in the field of military and civilian. Among them, unmanned helicopter has gained worldwide attention due to its flexible operation, vertical take-off and landing, and hovering ability. However, air disturbance, as a common flight environment, can inevitably affect the flight quality and navigation accuracy of UAV. Being a kind of rotorcraft with the special rotor structure, complex aerodynamic characteristics and strong coupling influence, the unmanned helicopter is inferior in control performance to the fixed wing UAV. Therefore, the unmanned helicopter with small flight speed is prone to be disturbed by strong airflow, which threatens the safety of flight in implementation of special tasks such as military mission, atmospheric monitoring, traffic monitoring, power line inspection, disaster relief, and forest fire prevention, et al.
In order to improve the position control precision of unmanned helicopter in complex airflow field, it is necessary to obtain the real-time and high-accuracy atmospheric disturbance information by means of measurement or estimation, which is used to compensate the disturbance in real-time. It is a key technology to improve navigation accuracy and enhance the ability to resist atmospheric disturbance of unmanned helicopter. Currently airborne wind field measurement is usually calculated with ground speed provided by GPS/inertial system and true airspeed provided by air data system. Because the measurement lag and measurement error of true airspeed, the wind speed of direct calculation cannot meet the aircraft requirements. Therefore, the method that can estimate strong airflow disturbance on the unmanned helicopter has become an urgent problem to be solved.
Our team has untaken the National Natural Science Foundation of China, with the name “Theory and Key Technology of the Autonomous Navigation and Control for Strong Airflow Interference on the Unmanned Helicopter ”(61533008). This project is based on the unmanned helicopter. It aims to solve the autonomous navigation and flight control problem due to the strong airflow turbulence in performing low altitude flight missions. The autonomous navigation method of the multi-source heterogeneous intelligent sensor information fusion and the method of the adaptive flight control under the strong airflow disturbance are both studied. Real-time atmospheric disturbance data estimation method of unmanned helicopter is one of the research contents of this project, which has important theoretical significance and application value.
A scheme of air disturbance data estimation for Unmanned Helicopter based on multi-source navigation data fusion is proposed in this paper. The information of navigation system and flight control system of the unmanned helicopter is used to establish the functional relationship between navigation data and atmospheric parameters. In addition, the multi-source information fusion algorithm is researched to achieve a real-time estimation of wind field information of unmanned helicopter. The state equation of the system is established by taking the air disturbance parameters as state variables. The measurement equation is established based on the inertial navigation, GNSS navigation and air data system information. In order to validate the effectiveness of the proposed atmospheric disturbance data estimation method for unmanned helicopter, we design a semi-physical simulation system which can repeat the flight path and the different flight state of unmanned helicopter. It can also simulate the disturbance of different wind fields to navigation system and the estimation process of air disturbance information to verify the proposed algorithm. The results show that the designed method can effectively estimate atmospheric disturbance information, and has wonderful performance with high precision, favorable stability and robustness.
The Navigation Research Center (NRC) of Nanjing University of Aeronautics and Astronautics (http://nrc.nuaa.edu.cn) is engaged in the research of navigation technology, and has done his very best on all source information fusion research. Up to now, a great deal of achievement has been made in the following fields: Global Satellite Positioning System, Smartphone / Pedestrian Navigation System, Strap-down Inertial Navigation System, Inertial Integrated Navigation System, Vision Aided Navigation System, Terrain Aided Navigation System, Fault-Tolerant Technique of Multi Inertial Navigation Subsystem, Modern Optimization Filtering Theory, Precision Measurement System and so on.
Keywords: Unmanned Helicopter; Wind Field Estimation; Multi-source Navigation Information Fusion; Inertial Navigation; GNSS.