基于无人机飞行参数的风场估算技术研究

利用无人机测量风速和风向已成为无人机应用的一项重点研究内容。基于无人机机载惯导系统、GPS系统和大气数据系统记录的飞行参数,建立飞行动力学模型,通过构建无迹卡尔曼滤波器的方法估算风速分量。与皮托-静压管测风法实测数据相比,在平飞状态下,该方法得到的风速估算结果曲线平滑,数值稳定,能够获得较准确的风速分量信息,为地面仿真及闭环试验提供较真实的风场环境参数。

Using unmanned air vehicle to measure wind speed and wind direction has become one of the key research contents of UAV application.A new method for wind field estimation by unscented kalman filter(UKF)is proposed.The dynamic functions were modeled using parameters from INS/GPS and air data system of an Unmanned Air Vehicle.The experimental results provided a smooth estimate of the wind velocity during level flight.It was shown that this method is c apable of providing a reasonable estimate of local wind field.