电讯技术2017，Vol.57Issue(2)：145-150,6.DOI:10.3969/j.issn.1001-893x.2017.02.004
相关性匹配蓝牙信标位置指纹库的室内定位
Indoor Localization of Bluetooth Beacon Position Fingerprint Based on Correlation Algorithm
摘要
Abstract
K-Nearest Neighbor algorithm,or"KNN"for short,often simply uses triangle centroid algorithm to locate. However,once the backlog site is close to a certain sample point, the accuracy of location will be greatly affected. Therefore,this paper proposes a correlation coefficient matching iBeacon position fingerprint algorithm. Firstly,through comparing the similar degree between undetermined point and a certain sample point of received signal strength indication( RSSI) fingerprint,it uses the test of data difference significance to test whether the backlog site data and fingerprint data is significantly correlated. Then,it takes the weigh―ted average of high correlation sample points to get the result. Experimental results show that the positioning accuracy within 2 m can be increased from 65% to 92% with the correlation coefficient matching fingerprint algorithm. Compared with traditional KNN localization algorithm,the proposed correlation matching algorithm has higher positioning precision,smaller calculation amount,and shorter positioning time.关键词
室内定位/蓝牙信标/位置指纹库/相关系数/显著性检验Key words
indoor positioning/bluetooth beacon/position fingerprint/correlation coefficient/significance testing分类
信息技术与安全科学引用本文复制引用
王艳丽,杨如民,余成波,孔庆达..相关性匹配蓝牙信标位置指纹库的室内定位[J].电讯技术,2017,57(2):145-150,6.基金项目
国家自然科学基金资助项目(61402063) （61402063）
重庆市科技人才培养计划(新产品研发团队)项目(CSJC2013KJRC-TDJS40012) （新产品研发团队）
重庆市高校优秀成果转化资助项目(KJZH14213) （KJZH14213）
