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基于区域划分的局部更新指纹定位算法 被引量:3

Local updating fingerprint localization algorithm based on region partition
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摘要 针对室内定位指纹数据库更新成本过高的问题,设计了一种通过区域划分进行局部更新指纹数据库的RFID(Radio Frequency Identification,射频识别技术)室内定位算法。该算法通过聚类算法将指纹地图分成若干个子区域,每个子区域选取一个代表点代表该子区域的指纹有效性,通过检测代表点的有效性来选择加权k近邻算法(Weighted k-Nearest Neighbor,WkNN)定位或子区域数据库的局部更新。实验结果表明,该算法在低成本的条件下极大限度地提高了定位精度和长期定位稳定性。 In order to solve the problem of high updating cost of indoor positioning fingerprint database, a RFID(Radio Frequency Identification)indoor positioning algorithm is designed to update the fingerprint database locally by region division. The algorithm divides the fingerprint map into several sub-regions by clustering algorithm, which selects a representative point for each sub-region to represent the fingerprint validity of the sub-region, and performs Weighted k-Nearest Neighbor(WkNN)algorithm or locally updates for sub-region database according to detecting the validity of all representative points. The experimental results show that the proposed algorithm can greatly improve the positioning accuracy and long-term positioning stability under the condition of low cost.
作者 杨斌 李灯熬 赵菊敏 YANG Bin;LI Deng’ao;ZHAO Jumin(College of Information and Computer,Taiyuan University of Technology,Jinzhong,Shanxi 030600,China)
出处 《计算机工程与应用》 CSCD 北大核心 2018年第17期56-61,共6页 Computer Engineering and Applications
基金 国家高技术研究发展计划(863)(No.2015AA016901) 国家自然科学基金面上项目(No.61572346 No.61572347 No.61772358) 山西省国际科技合作项目(No.201603D421012)
关键词 室内定位 指纹数据库 射频识别技术(RFID) 聚类算法 加权k近邻算法(WkNN) indoor positioning fingerprint database Radio Frequency Identification(RFID) clustering algorithm Weighted k-Nearest Neighbor(WkNN)
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  • 1方震,赵湛,郭鹏,张玉国.基于RSSI测距分析[J].传感技术学报,2007,20(11):2526-2530. 被引量:265
  • 2崔莉,鞠海玲,苗勇,李天璞,刘巍,赵泽.无线传感器网络研究进展[J].计算机研究与发展,2005,42(1):163-174. 被引量:730
  • 3李洁,高新波,焦李成.基于特征加权的模糊聚类新算法[J].电子学报,2006,34(1):89-92. 被引量:113
  • 4李伟章.全球定位系统(GPS)介绍[J].无线电技术与信息,2006(4):4-7. 被引量:2
  • 5张洁颖,孙懋珩,王侠.基于RSSI和LQI的动态距离估计算法[J].电子测量技术,2007,30(2):142-145. 被引量:58
  • 6MacQueen J.Some Methods for Classification and Analysis of Multivariate Observations[C]//Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability,1967.
  • 7Wang Wei,Yang Jiong,Muntz R.STING:A Statistical Information Grid Approach to Spatial Data Mining[C]//Proc.of the 23rd International Conference on Very Large Data Bases,1997.
  • 8Agrawal R,Gehrke J,Gunopulcs D.Automatic Subspace Clustering of High Dimensional Data for Data Mining Application[C]//Proc.of ACM SIGMOD Intconfon Management on Data,Seattle,WA,1998:94-205.
  • 9Guha S,Rastogi R,Shim K.Cure:An Efficient Clustering Algorithm for Large Database[C]//Proc.of ACM-SIGMOND Int.Conf.Management on Data,Seattle,Washington,1998:73-84.
  • 10Savarese C,Rabaey J M,Beutel J.Locationing in distributed ad-hoc wireless sensor network[C]//Proceedings of the 2001 IEEE International Conference on Acoustics,Speech,and Signal.Piscataway,USA:IEEE Signal Processing Society,2001:2037-2040.

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