基于合作目标和视觉的无人飞行器全天候自动着陆导引关键技术

 GPS受他国控制和易受干扰对基于该导航系统的无人飞行器导航和着陆具有潜在危险，为了使其安全自动着陆，提出通过在着陆跑道(广场或公路)上预设具有受控发射红外光的地面合作目标，实现无人飞行器的视觉全天候自动精确着陆新技术。首先研究得到切实可行的工作过程;然后研制了合作目标，通过理论分析和实验得出，无论能见度高低，8~12 μm中远红外视觉系统探测到的合作目标图像质量远优于可见光视觉系统，研究得到合作目标和背景的温差在170~200 ℃时，成像效果最好。在识别研究中发现，基于传统的不变矩算法对合作目标的识别可靠性稍差，为了进一步准确地识别合作目标，又提出了基于方向链码的合作目标识别算法，该方法的耗时为不变距的96%，但是识别的可靠性比前者有显著提高。

Key Technology of Unmanned Aerial Vehicle's Navigation and Automatic Landing in All Weather Based on the Cooperative Object and Infrared Computer Vision

GPS is controlled by other country and jammed easily, it is the potential danger to the unmanned aerial vehicle ( UAV) based on GPS. In order to make it land automatically and safely, a novel method of UAV automatic landing’s guidance in all weather is proposed based on the cooperative object that is controlled to radiate infrared on the landing runway (highway or square available) and infrared computer vision. The infrared (8~12 μm) visual system is adopted as the video gathering system by analyzing the permeation ratio of light-wave and atmospheric windows and some experiments.The cooperative object is developed,and its infrared image is better when its temperature is higher 170~200℃ than the temperature of background.Then the traditional moment invariant recognition algorithm is studied to recognize the cooperative object,but the reliability of recognition is low.For improving reliability and accuracy,a sort of recognition algorithm based on direction code for the cooperative object is put forward.The experimental results show that the time consumption of this new recognition algorithm is 96% the time consumption of the traditional moment invariant recognition algorithm,and the recognition reliability is improved obviously.