Altitude Information Fusion of Miniature Unmanned Helicopter Based on LSSVM

摘要：

The miniature unmanned helicopter exhibits a highly nonlinear, high dimensional feature space and uncertain conditions. This paper describes an altitude information fusion method based on Least Squares Support Vector Machine (LSSVM). This method uses small sample without human experience, modeling by the measured data from the GPS and INS. The simulations results have demonstrated the modeling well show the helicopters actual altitude in the hover state.

关键词： Least Squares Support Vector Machine (LSSVM) information fusion miniature unmanned helicopter altitude

作者: Li Jing Wu Jiande Fan Yugang Wang Xiaodong Chen Weili

作者单位: Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kun Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kun

会议类型: 国际会议

会议名称: 2010 Third International Symposium on Knowledge Acquisition and Modeling(第三届知识获取与建模国际研讨会 KAN 2010)

会议地点: 武汉

会议语种:英文

页码: 262-264

在线出版日期: 2010-10-20（万方平台首次上网日期，不代表论文的发表时间）