%0 Journal Article
%T Horizon detection algorithm in extended Kalman filter framework<br>扩展Kalman滤波框架下的地平线检测算法
%A XU Wei-jie
%A LI Ping
%A HAN Bo
%A <br>徐伟杰
%A 李平
%A 韩波
%J 控制理论与应用
%D 2012
%I 
%X To detect the horizon in the pose measurement for a vision-based unmanned aerial vehicle (UAV), we propose a horizon-extraction algorithm which combines the image processing and extended Kalman filter (EKF). The image processing part extracts straight lines from the image edges as candidates of horizon; and then, it uses the dark channel prior of the image to decide the horizon. The EKF part of the algorithm combines a horizon line observation model with a fuselage rotation model to obtain the predicted observation and innovation covariance, which are employed for judging whether a correct horizon is detected. Correction will be carried out when wrong horizon is detected. The experimental results show that the proposal algorithm can effectively detect the horizon, and is robust to complex scenes.
%K horizon detection
%K edge extraction
%K dark channel prior
%K unmanned aerial vehicle
%K attitude estimation<br>地平线检测
%K 边缘检测
%K 暗原色先验
%K 无人机
%K 姿态估计
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=05C671FE727BA759D509E6EA1F8F6C86&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=0B39A22176CE99FB&sid=4966445AEEBA9556&eid=CA5852BD1A173B3A&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=0