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首页> 外文会议>AIAA guidance, navigation, and control conference;AIAA SciTech forum >Model Aided Estimation of Angle of Attack, Sideslip Angle, and 3D Wind without Flow Angle Measurements
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Model Aided Estimation of Angle of Attack, Sideslip Angle, and 3D Wind without Flow Angle Measurements

机译：在没有流动角测量的情况下，模型辅助估计迎角，侧滑角和3D风

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Accurate estimations of the relative movement of the aircraft with respect to the surrounding air are critical to flight performance and aircraft safety. This paper proposes two novel aircraft-model-aided extended Kalman filters (EKFs), a 2-state EKF and a 9-state EKF. The proposed filters can estimate angle of attack, sideslip angle, and 3D wind without using direct flow angle measurements such as a multi-hole pitot-tube or mechanical vanes. Both simulation and small unmanned aerial vehicle (UAV) flight test data are used to validate the methods. Experimental results show that the 2-state EKF can estimate angle of attack (AOA) and angle of sideslip (AOS) with around 2 degrees root mean square errors under aggressive maneuvers compared with a high-fidelity 5-hole pitot tube. The 9-state EKF can estimate 3D wind velocities with comparable mean values as a sonic wind anemometer from a ground weather station.
机译：飞机相对于周围空气的相对运动的准确估计对于飞行性能和飞机安全至关重要。本文提出了两种新颖的飞机模型辅助扩展卡尔曼滤波器（EKF），即2状态EKF和9状态EKF。所提出的滤波器可以估计迎角，侧滑角和3D风，而无需使用直接流量角测量（例如多孔皮托管或机械叶片）。仿真和小型无人机飞行测试数据均用于验证方法。实验结果表明，与高保真5孔皮托管相比，二状态EKF可以估计在激进操纵下的攻角（AOA）和侧滑角（AOS）均方根误差约为2度。 9州EKF可以估算3D风速，平均值与地面气象站的声波风速仪相当，具有可比的平均值。

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