靳赛州,陈国良,张超,王轩,王俊鹏,王睿

• 1:中国矿业大学自然资源部国土环境与灾害监测重点实验室
• 2:中国矿业大学环境与测绘学院

摘要(Abstract)：

针对蓝牙定位精度差、耗时长等问题,该文提出一种基于区域优选的自适应蓝牙指纹定位算法。离线阶段,采用粗细粒度划分建立关于RSSI采样点位置映射的指纹库;在线阶段,根据信标距离和RSSI的关系,提出加权欧氏距离和区域优选算法,有效地克服了定位稳定性差和耗时长的问题,定位效率提高了40%,在在线定位过程中,采用自适应K值定位算法,有效地剔除了离定位点较远的点,提高了定位的精度与稳定性。在5 m×9 m的区域内进行定位精度测试,结果表明:蓝牙定位平均定位误差为0.92 m,定位误差均在2 m以内,90%的点定位精度优于1.5 m。

关键词(KeyWords)： 位置指纹匹配技术;蓝牙定位;加权欧氏距离;区域优选;自适应K值

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划项目(2016YFB0502105);; 国家自然科学基金项目(41371423);; 江苏省自然科学基金项目(BK20161181);; 江苏高校品牌专业建设工程资助项目(PPZY2015B144)

作者(Author): 靳赛州,陈国良,张超,王轩,王俊鹏,王睿

DOI: 10.16251/j.cnki.1009-2307.2020.08.008

参考文献(References)：

• [1] 宁津生,姚宜斌,张小红.全球导航卫星系统发展综述[J].导航定位学报,2013,1(1):3-8.(NING Jinsheng,YAO Yibin,ZHANG Xiaohong.Review of the development of global satellite navigation system[J].Journal of Navigation and Positioning,2013,1(1):3-8.)
• [2] 陈锐志,陈亮.基于智能手机的室内定位技术的发展现状和挑战[J].测绘学报,2017,46(10):1316-1326.(CHEN Ruizhi,CHEN Liang.Indoor positioning with smartphones:the state-of-the-art and the challenges[J].Acta Geodaetica et Cartographica Sinica,2017,46(10):1316-1326.)
• [3] KRUMM J,HORVITZ E.LOCADIO:inferring motion and location from Wi-Fi signal strengths[C]//International Conference on Mobile and Ubiquitous Systems:Networking and Services.[S.l.]:IEEE,2004:4-13.
• [4] HALLBERG J,NILSSON M,SYNNES K.Positioning with Bluetooth[C]//10th International Conference on Telecommunications.[S.l.]:IEEE,2003:954-958.
• [5] ZHENG L,DEHAENE W,GIELEN G.A 3-tier UWB-based indoor localization scheme for ultra-low-power sensor nodes[J].IEEE Transactions on Wireless Communications,2009,8(6):2813-2818.
• [6] FANG S,WANG C,HUANG T,et al.An enhanced ZigBee indoor positioning system with an ensemble approach[J].IEEE Communications Letters,2012,16(4):564-567.
• [7] HUANG Y,LYU S,WANG J,et al.The topology analysis of reference tags of RFID indoor location system[C]//2009 3rd IEEE International Conference on Digital Ecosystems and Technologies.[S.l.]:IEEE,2009:313-317.
• [8] 李昊.位置指纹定位技术[J].山西电子技术,2007(5):84-87.(LI Hao.Indoor position techniques based on location fingerprint[J].Shanxi Electronic Technology,2007(5):84-87.
• [9] WANG Q,FENG Y,ZHANG X,et al.IWKNN:an effective Bluetooth positioning method based on Isomap and WKNN[J].Mobile Information Systems,2016(1):1-11.
• [10] 毕京学,甄杰,汪云甲,等.高斯函数定权的改进KNN室内定位方法[J].测绘通报,2017(6):9-12.(BI Jingxue,ZHEN Jie,WANG Yunjia,et al.The method of enhanced Gaussian function weighted KNN indoor positioning[J].Bulletin of Surveying and Mapping,2017(6):9-12.)
• [11] 杨勇明.基于分步的位置指纹定位算法研究[J].电子科技,2018,31(11):60-64.(YANG Yongming.Study on positioning algorithm based on step by step fingerprint location[J].Electronic Science and Technology,2018,31(11):60-64.)
• [12] 曹晓祥,陈国良.一种改进的组合定权的指纹定位算法[J].测绘通报,2018(2):6-10.(CAO Xiaoxiang,CHEN Guoliang.An improved fingerprint indoor localization algorithm based on combination weight[J].Bulletin of Surveying and Mapping,2018(2):6-10.)
• [13] 刘冰,李文书.基于余弦相似度的指纹匹配算法的室内定位方法[J].科技通报,2017,33(3):198-202.(LIU Bing,LI Wenshu.Indoor positioning method based on cosine similarity of fingerprint matching algorithm[J].Bulletin of Science and Technology,2017,33(3):198-202.)
• [14] WANG Q,SUN R,ZHANG X,et al.Bluetooth positioning based on weighted K-nearest neighbors and adaptive bandwidth mean shift[J].International Journal of Distributed Sensor Networks,2017,13(5):1-8.
• [15] 羊宗灏,程凯,周宝定,等.基于RSS相关性的位置指纹室内定位方法[J].智能计算机与应用,2017,7(2):8-13.(YANG Zonghao,CHENG Kai,ZHOU Baoding,et al.Received signal strength correlation based location fingerprint indoor localization[J].Intelligent Computer and Applications,2017,7(2):8-13.)
• [16] BAHL P,PADMANABHAN V N.RADAR:an in-building RF-based user location and tracking system[C]//Nineteenth Joint Conference of the IEEE Computer and Communications Societies.[S.l.]:IEEE,2000:775-784.
• [17] SHIN B,LEE J H,LEE T,et al.Enhanced weighted K-nearest neighbor algorithm for indoor Wi-Fi positioning systems[C]//International Conference on Computing Technology and Information Management.[S.l.]:IEEE,2012:574-577.
• [18] JACCARD P.The distribution of the flora in the alpine zone[J].New Phytologist,2010,11(2):37-50.
• [19] CASO G,DE NARDIS L,DI BENEDETTO M.Frequentist inference for WiFi fingerprinting 3D indoor positioning[C]//IEEE International Conference on Communication Workshop.[S.l.]:IEEE,2015:809-814.
• [20] 吉彩云,袁明辉,李瑞祥,等.基于K-means的室内定位加权优化k-NN算法[J].电子测量技术,2018,41(10):66-69.(JI Caiyun,YUAN Minghui,LI Ruixiang,et al.Indoor positioning based on K-means and the weighted optimized k-NN algorithm[J].Electronic Measurement Technology,2018,41(10):66-69.)