Currently, most of the studies on unmanned aerial vehicle (UAV) automatic landing systems mainly depend on image information to determine the landing location. However, the system requires a camera, a gimbal system and a separate image-processing device, which increases the weight and power consumption of the UAV, resulting in a shorter flight time. In addition, a large amount of computation and slow reaction speed can cause the camera to miss a proper landing moment. To solve these problems, in this study, the moving direction and relative distance between an object and the automatic landing system were measured using a receive signal strength indicator of the radio-frequency (RF) signal. To improve the movement direction and relative distance estimation accuracy, the noise in the RF signal was minimised using a low pass filter and moving average filter. Based on the filtered RF signal, the acceleration of the multicopter to reach the object was estimated by adopting the proportional navigation algorithm. The performance of the proposed algorithm for precise landing on a moving vehicle was demonstrated through experiments.

目前，大多数关于无人机自动着陆系统的研究主要依靠图像信息来确定着陆位置。然而，该系统需要相机、万向架系统和单独的图像处理设备，这增加了无人机的重量和功耗，导致飞行时间缩短。另外，计算量大、反应速度慢也会导致相机错过合适的着陆时刻。为了解决这些问题，在本研究中，使用射频（RF）信号的接收信号强度指示器来测量物体与自动着陆系统之间的移动方向和相对距离。为了提高移动方向和相对距离估计精度，使用低通滤波器和移动平均滤波器将射频信号中的噪声降至最低。基于滤波后的射频信号，采用比例导航算法估计多旋翼飞行器到达目标的加速度。通过实验证明了所提出的在移动车辆上精确着陆的算法的性能。