[1]戴洪德,邹 杰,徐胜红,等.含预测和容错的自适应Kalman目标跟踪[J].南京理工大学学报(自然科学版),2015,39(01):108-114.
 Dai Hongde,Zou Jie,Xu Shenghong,et al.Adaptive Kalman filter combined with prediction and fault tolerance for target tracking[J].Journal of Nanjing University of Science and Technology,2015,39(01):108-114.
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含预测和容错的自适应Kalman目标跟踪
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
39卷
期数:
2015年01期
页码:
108-114
栏目:
出版日期:
2015-02-28

文章信息/Info

Title:
Adaptive Kalman filter combined with prediction and fault tolerance for target tracking
作者:
戴洪德12邹 杰2徐胜红1王永庭2吴晓男1吴光彬1
1.海军航空工程学院 控制工程系,山东 烟台 264001; 2.光电控制技术重点实验室,河南 洛阳 471009
Author(s):
Dai Hongde12Zou Jie2Xu Shenghong1Wang Yongting2 Wu Xiaonan1Wu Guangbin1
1.Department of Control Engineering,Naval Aeronautical and Astronautical University,Yantai 264001,China; 2.Science and Technology on Electron-optic Control Laboratory,Luoyang 471009,China
关键词:
目标跟踪 Kalman滤波 自适应 预测 估计 容错 抗干扰 在线匹配 新息协方差
Keywords:
target tracking Kalman filter adaptive prediction estimation fault tolerant anti-interference on-line matching innovation covariance
分类号:
TP391.41
摘要:
针对模型不准确时,传统Kalman滤波目标跟踪算法精度有限甚至发散的问题,研究了基于新息协方差在线匹配技术的自适应Kalman滤波算法,提高跟踪精度; 并以Kalman滤波估计的目标位置为基础,利用一步Kalman预测得到下一时刻目标可能的位置范围,避免对整幅后帧图像进行遍历搜索,减小了计算量; 为了避免存在干扰时异常量测对目标跟踪的影响,研究了量测信息异常检测算法,以Kalman预测的量测代替异常量测,增强抗干扰能力。实验证明,所提算法能够有效提高目标跟踪的精度和鲁棒性。
Abstract:
An adaptive Kalman filter,based on the online matching of innovation covariance,is presented to overcome the problem of accuracy degrade or even divergence when there exists tremendous modeling errors and to improve the accuracy of target tracking.The area where the target may appear at the next epoch is predicted by one-step Kalman predictor,based the position of the target estimated by Kalman filter at present to avoide searching the whole image to find the target and to reduce the calculation burden.Abnormal measurement detection is also studied and the abnormal measurements are replaced by the Kaman predicted measurement,to avoid the disturbance caused by the abnormal measurement and to increase the anti-interference ability.Experimental results show that the accuracy and robustness of target tracking can be improved by the algorithm presented here.

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备注/Memo

备注/Memo:
收稿日期:2013-10-12 修回日期:2014-06-11
基金项目:国家自然科学基金(61203168); 航空科学基金(20135184007)
作者简介:戴洪德(1981-),男,博士,副教授,主要研究方向:惯性技术与组合导航,信息融合,E-mail:dihod@126.com。
引文格式:戴洪德,邹杰,徐胜红,等.含预测和容错的自适应Kalman目标跟踪[J].南京理工大学学报,2015,39(1):108-114.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2015-02-28