基于分步的位置指纹定位算法研究
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摘要
针对LANDMARC室内定位算法产生数据冗余的问题,文中提出一种基于分步的位置指纹定位算法。离线训练阶段,通过合理布置粗粒度点与细粒度点建立位置与信号强度之间的指纹图,在线定位阶段,将实时测得的信号强度通过与指纹图对比进行粗定位和精定位。实验表明,分步的位置指纹定位算法在保证定位精度的同时,有效减少了数据计算量和传输量,满足定位的实时性要求,适用于室内定位等领域。
Aiming at the data redundancy of LANDMARC indoor positioning algorithm,a positioning algorithm based on step by step fingerprint location was proposed in the study. At the off-line training stage,fingerprint diagram between the location and the signal strength was established through reasonable arrangement of the coarse-grain point and the fine-grain point. At online positioning stage,the coarse positioning and fine positioning were measured through the comparison between real-time signal strength and fingerprint diagram. Experiments showed that step by step location fingerprinting algorithm not only kept the positioning accuracy,but also reduced the amount of computation and transmission of data. The algorithm met the real-time requirements of positioning and was suitable for indoor positioning and other fields.
Aiming at the data redundancy of LANDMARC indoor positioning algorithm,a positioning algorithm based on step by step fingerprint location was proposed in the study. At the off-line training stage,fingerprint diagram between the location and the signal strength was established through reasonable arrangement of the coarse-grain point and the fine-grain point. At online positioning stage,the coarse positioning and fine positioning were measured through the comparison between real-time signal strength and fingerprint diagram. Experiments showed that step by step location fingerprinting algorithm not only kept the positioning accuracy,but also reduced the amount of computation and transmission of data. The algorithm met the real-time requirements of positioning and was suitable for indoor positioning and other fields.
引文
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[15] Phimmasean S,Chuenurajit T,Cherntonomwong P. Indoor localization system based on fingerprint technique using RFID passive tag[C]. Honolulu:10thInternational Conference on Electrical Engineering/Electronics,Computer,Telecommunications and Information Technology(ECTI-CON),IEEE,2013.
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[2]王力.物联网技术及其在宝钢的应用[J].控制工程,2013,20(6):1147-1151.
[3]孙瑜,范平志.射频识别技术及其在室内定位中的应用[J].计算机应用,2005,25(5):1205-1208.
[4]西梁.基于ARM平台的RFID室内定位的研究[D].济南:山东大学,2014.
[5] Ni L M,Liu Y,Lau Y C,et al. LANDMARC:indoor location sensing using active RFID[C]. Texas:International Conference on Pervasive Computing and Communications,IEEE,2003.
[6] Bergemann S,Sieck J. Adopting the LANDMARC positioning system for 2. 4 GHz band[C]. Madrid:Fifth Uk Sim European Symposium on Computer Modeling and Simulation,IEEE,2011.
[7]史伟光,刘开华,于洁潇,等.基于加权欧式算子的射频识别定位算法[J].计算机工程,2011,37(9):22-24.
[8] Li B,Salter J,Dempster A G,et al. Indoor positioning techniques based on wireless LAN[C]. California,USA:Lan First IEEE International Conference on Wireless Broadband&Ultra Wideband Communications,2006.
[9]张世龙.基于动态划分的仓储环境RFID定位方法研究[D].武汉:武汉理工大学,2015.
[10]吴王润.基于改进LANDMARC算法的RFID室内定位系统研究与实现[D].长沙:中南大学,2014.
[11]谈飞.基于有源RFID的指纹定位及仓库管理系统分析与实现[D].上海:复旦大学,2010.
[12] Jingwangsa T,Soonjun S,Cherntanomwong P. Comparison between innovative approaches of RFID based localization using fingerprinting techniques for outdoor and indoor environments[C]. Cambridge:12thInternational Conference on Advanced Communication Technology(ICACT),IEEE,2010.
[13]Fu Q,Retscher G. Active RFID trilateration and location fingerprinting based on RSSI for pedestrian navigation[J].Journal of Navigation,2009,62(2):323-340.
[14]陈聪传,程良伦.区域细化的RFID室内定位算法[J].计算机应用与软件,2011,28(1):50-52.
[15] Phimmasean S,Chuenurajit T,Cherntonomwong P. Indoor localization system based on fingerprint technique using RFID passive tag[C]. Honolulu:10thInternational Conference on Electrical Engineering/Electronics,Computer,Telecommunications and Information Technology(ECTI-CON),IEEE,2013.
[16]普赖斯. C#数据库编程从入门到精通[M].北京:电子工业出版社,2003.
[17]Xiang Z,Wang D,Xiang Z,et al. Performance evaluation of active RFID real time location system based on RSSI[C].Cambridge:Proceedings of the 2010 IEEE International Conference on Progress in Informatics and Computing,2010.