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卡尔曼滤波在室内定位系统实时跟踪中的应用 被引量：29

Application of Kalman Filter in Indoor Positioning System for Real-Time Tracking
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摘要 为了解决室内定位系统实时跟踪应用中所估算的用户位置方差较大,用户位置移动不平缓这一难题,提出了一种基于卡尔曼滤波的室内定位方法.首先利用最近邻居法估算用户的位置坐标,然后再利用卡尔曼滤波算法对用户的估算位置坐标进行滤波处理,以提高室内定位系统的性能和稳定性.实验结果表明,卡尔曼滤波算法可以将2 m以内85%的定位精度进一步提高到93%,3 m以内95%的定位精度提高到98%,改进效果明显而且稳定. In this paper, an indoor positioning technology based on Kalman filter algorithm is proposed to solve the problem that the standard deviation of forecasted user location is larger, and the move of user location is not smooth at real-time tracking stage. Firstly, nearest neighbor method is utilized to forecast the location of user, then the Kalman filter is used to filter the forecasted user location in order to further improve the performance and stability of indoor positioning system. Experimental results illustrate that the proposed kalman filter can increase the 85% accuracy of estimation with a precision of 2 meters to 93%,and increase 95% accuracy of estimation with a precision of 3 meters to 98%. Therefore, the proposed Kalman filter algorithm in this paper can improve the positioning accuracy remarkably and stably.
作者 赵永翔 周怀北 陈淼 温斌
机构地区 武汉大学软件工程国家重点实验室 武汉大学电子信息学院
出处 《武汉大学学报（理学版）》 CAS CSCD 北大核心 2009年第6期696-700,共5页 Journal of Wuhan University:Natural Science Edition
基金 国家高技术研究发展计划(863)项目(2007AA12Z324 2009AA12Z324) 国家重点基础研究发展规划(973)项目(2009CB320401)
关键词 无线局域网 室内定位 位置指纹 卡尔曼滤波 实时跟踪 wireless LANs indoor positioning location fingerprinting Kalman filter real-time tracking
分类号 TP301.6 [自动化与计算机技术—计算机系统结构] TP303.17 [自动化与计算机技术—计算机系统结构]
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参考文献15

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二级参考文献31

  • 1Hazas M,Scott J,Krumm J.Location-aware computing comes of age.Computer,2004,37(2):95～97
  • 2Want R,Hopper A,Falcao V,et al.The active badge location system.ACM Transactions on Office Information Systems (TOIS),1992,10(1):91～102
  • 3Ward A,Jones A,Harper A.A new location technique for the active office.IEEE Personal Communications,1997,4(5):42～47
  • 4Priyantha N B,Chakraborty A,Balakrishnan H.The cricket location-support system.In:Proceedings of MOBICOM 2000,Boston,MA,ACM,ACM Press,August 2000.32～43
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  • 10Youssef M,Agrawala A,Shankar A U.WLAN Location Determination via Clustering and Probability Distributions.In:IEEE International Conference on Pervasive Computing and Communications (PerCom)2003,Fort Worth,Texas,March,2003

共引文献65

同被引文献235

引证文献29

二级引证文献193

武汉大学学报（理学版）
2009年 第6期

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