首页 | 官方网站   微博 | 高级检索  
     

红外序列图像目标跟踪的自适应Kalman滤波方法
引用本文:高璐,张大志,田金文.红外序列图像目标跟踪的自适应Kalman滤波方法[J].红外与激光工程,2007,36(5):729-732.
作者姓名:高璐  张大志  田金文
作者单位:华中科技大学,多谱信息处理技术国防重点实验室,湖北,武汉,430074
摘    要:提出了一种用于动态序列图像目标跟踪的自适应Kalman滤波方法。该方法用函数估计的思想估计目标的当前运动模型,同时实时修改滤波器的统计模型,并将最小二乘支持向量机应用于对当前目标运动模型的估计。实验表明,此种改进的Kalman滤波器的算法在跟踪机动目标时具有良好的性能。

关 键 词:目标跟踪  红外序列图像  Kalman滤波  自适应滤波  运动模型估计  最小二乘支持向量机
文章编号:1007-2276(2007)05-0729-04
收稿时间:2006/11/8
修稿时间:2006-11-082007-02-01

Moving object tracking based on adaptive Kalman filter
GAO Lu,ZHANG Da-zhi,TIAN Jin-wen.Moving object tracking based on adaptive Kalman filter[J].Infrared and Laser Engineering,2007,36(5):729-732.
Authors:GAO Lu  ZHANG Da-zhi  TIAN Jin-wen
Affiliation:State Laboratory of Multi-spectral Information Processing Technologies, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract:Target tracking has been widely applied in military and civil fields. An adaptive Kalman filter algorithm is described for moving object tracking. Such approach uses function estimation strategy to estimate the movement models of the target. LS-SVM is applied to estimate the movement models of the target and the statistical models of the system. Experimental results show that the approach has a satisfactory tracking performance in case of moving object tracking.
Keywords:Object tracking  Infrared imagery series  Kalman filter  Adaptive filter  Moving model estimation  LS-SVM
本文献已被 维普 万方数据 等数据库收录!
点击此处可从《红外与激光工程》浏览原始摘要信息
点击此处可从《红外与激光工程》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号