To address standoff target tracking using a fixed-wing UAV in unknown background wind, a wind estimation based on Unscented Kalman Filter (UKF) is proposed. In the paper, UAV dynamic model and target state estimation are constructed, and Lyapunov vector field guidance (LVFG) framework is introduced to achieve standoff target tracking. The unknown target state and wind dynamic model have seldom been discussed for standoff tracking in the previous research. Therefore, two typical wind dynamic models with Dryden and Davenport spectrums are constructed for the target in the high altitude or near the ground. Then, the unscented transformation is adopted to estimate the position of UAV under guidance command generated by LVFG and saturation constraint. A wind state estimation method based on UKF is proposed to improve performance of standoff tracking. Simulated and realistic ground vehicle trajectories are used to demonstrate the availability and effectiveness of the proposed method for different wind dynamic models.

中文翻译：

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基于无迹卡尔曼滤波器的风估计用于使用固定翼无人机进行防区外目标跟踪

为了解决在未知背景风中使用固定翼无人机进行防区外目标跟踪的问题，提出了一种基于无迹卡尔曼滤波器（UKF）的风估计。论文构建了无人机动力学模型和目标状态估计，并引入了李雅普诺夫矢量场导（LVFG）框架实现对峙目标跟踪。以往的研究中很少讨论未知目标状态和风动力学模型用于对峙跟踪。因此，针对高空或近地目标构建了两个典型的具有 Dryden 和 Davenport 谱的风动力学模型。然后，采用无味变换估计无人机在LVFG和饱和约束产生的制导命令下的位置。提出了一种基于UKF的风态估计方法，以提高对距跟踪的性能。