模糊联合卡尔曼滤波器在机场泊位引导系统中的应用  

Application of Fuzzy Federal Kalman Filtering in the Airport Automatic Docking Guidance System

作　　者：李国[1] 杨国庆[1] 韩广东[2] 高庆吉[2] 

机构地区：[1]南京航空航天大学信息科学与技术学院,江苏南京210016 [2]中国民航大学机器人研究所,天津300300

出　　处：《小型微型计算机系统》2008年第7期1320-1323,共4页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(60472125)资助;民航总局基金项目(MY0421805)资助

摘　　要：提出一种应用于机场泊位引导系统的模糊联合卡尔曼滤波算法,通过将视觉和激光传感器的信息融合,解决了基于单一传感器引导系统可靠性不高的问题.该算法监视测量值是否发生较大波动,应用模糊推理系统调整各局部滤波器输出状态向量的协方差阵,在线修正全局滤波器内各融合信息的权值,降低了波动数据对估值的影响.实验证明该算法对测量值的波动有较强的鲁棒性,提高了机场泊位引导系统的可靠性.This paper presents an algorithm of Fuzzy Federal Kalman Filtering used for the Airport Automatic Docking Guidance System. Information of vision and laser sensors is fused to improve the reliability of the single-sensor system. Monitoring the fluctuation of the measure values, adjusting the state vector covariance of each local filtering in use of the Fuzzy Inference Sys- tem （FIS） and modifying the weight of each fusion data online in main filtering, the algorithm reduces the disturbance of the fluctuation data. The results of the experiment prove that this algorithm has good robustness for fluctuation of the measure values and improves the reliability of the system.

关 键 词：模糊推理 联合卡尔曼滤波 泊位引导系统 融合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]