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为了模拟紊流风场下的无人机飞行状态响应,减小紊流风场对无人机飞行速度的影响,使用数值法建立了紊流风场有色噪声模型,生成了符合大气紊流相关特性的紊流风场并对其进行数值仿真。在此基础上,通过状态扩增处理将系统噪声白化,设计出一种基于有色噪声的无人机飞行速度卡尔曼滤波器,该滤波器解决了基本卡尔曼滤波仅适用于白噪声的情况。仿真结果表明,使用此滤波器可有效减小紊流风场对无人机飞行速度的影响,进而满足飞行速度控制输入的精度要求。
In order to simulate the UAV’s flight state response in turbulent wind field and reduce the influence of turbulence wind field on the UAV flight speed, a colored noise model of turbulent wind field was established by numerical method and a turbulence-related turbulence- Flow field and its numerical simulation. Based on this, the system noise is whitenned by state amplification processing to design a UAV flight velocity Kalman filter based on colored noise, which solves the basic Kalman filter only suitable for white noise. The simulation results show that using this filter can effectively reduce the impact of turbulence wind field on the UAV flight speed, and then meet the accuracy requirements of the flight speed control input.