首页 | 本学科首页   官方微博 | 高级检索  
     

动态加权和测量方差时变的多传感器融合算法
引用本文:胡振涛,刘先省. 动态加权和测量方差时变的多传感器融合算法[J]. 计算机测量与控制, 2005, 13(8): 877-880
作者姓名:胡振涛  刘先省
作者单位:河南大学,计算机与信息工程学院,河南,开封,475001;河南大学,计算机与信息工程学院,河南,开封,475001
基金项目:国家自然科学基金(60272024),河南省高校杰出科研人才创新工程项目(2003KYCX003),河南省高校创新人才培养工程。
摘    要:在基于卡尔曼滤波及其一些改进算法中,由于测量方差预先设定,从而导致滤波发散和信息资源的浪费,为此提出了一种动态加权下测量方差时变的多传感器融合算法。该算法依据各传感器当前时刻的滤波精度合理地分配权值,同时测量方差的时变特性使得每次测量信息得到充分的利用。仿真结果表明该算法显著地提高了对机动目标的跟踪效果并具有实时性的优点。

关 键 词:多传感器融合  测量方差  Kalman滤波
文章编号:1671-4598(2005)08-0877-04
修稿时间:2004-11-11

Algorithm of Multi-sensor Fusion Based on Dynamic weight and Time-varying Measurement Variance
Hu Zhentao,Liu Xianxing. Algorithm of Multi-sensor Fusion Based on Dynamic weight and Time-varying Measurement Variance[J]. Computer Measurement & Control, 2005, 13(8): 877-880
Authors:Hu Zhentao  Liu Xianxing
Abstract:In the algorithm based on Kalman filter and its extension, the presupposition of the measurement variance leads to filter divergence and waste of information, Hence , a new algorithm of multi-sensor fusion is presented based on time-varying of measurement variance and dynamic weight. The algorithm reasonably distributes weight value according to the filter accuracy renewed of each sensor, meanwhile, the specific property of time-varying in measurement variance makes innovation obtained each time sufficiently utilized. The simulation shows that this algorithm can obviously improve the efficiency of maneuvering target tracking on the base of possessing real-time merit.
Keywords:multi-sensor fusion  measurement variance  Kalman filter
本文献已被 CNKI 维普 万方数据 等数据库收录!
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