基于GPS、磁罗盘与大气数据计算机的无人机风估计

针对无人机实时航路规划及适应环境变化的自主能力发展需求,提出了一种新的风估计与空速校准的方法;该方法基于GPS接收机、大气计算机和磁罗盘等传感器实现;针对定常风模型,风速、风向能够利用地速、风速和空速之间的速度矢量三角形关系计算得到；采用无导扩展卡尔曼滤波(DEKF),估计风场信息以及真空速的比例校准系数；利用某型无人机数字仿真平台,在2D定常风条件下进行了全过程自主飞行仿真；仿真结果表明:该方法在航路跟随的直线段、转弯段均能准确估计。

Wind Estimation for UAV Based on GPS, Magnetic Compass and Air Data Computer

Aiming at the requirements of real-time path planning and autonomous capability for adapting to the environmental changes of Unmanned Aerial Vehicle (UAV), a new method for wind estimation and airspeed calibration is proposed. Based on the information of GPS receiver, air data computer and magnetic compass, the method is implemented. Aiming at constant wind mode, the wind speed and wind direction can be estimated using velocity triangle vector between ground speed, wind speed and airspeed. A Derivative-free extended Kalman filter (DEKF) is applied to estimate wind parameters and scaling factor of airspeed. Using a digital simulation platform for Unmanned Aerial Vehicle (UAV), an entire autonomic flight simulation were achieved in 2D wind field. Simulations results show that wind speed and wind direction can be accurately estimated both in straight line and turning segment during the path tracking by using the method.