| 蓝牙4.0标准规范下的模糊指纹定位算法 |
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| 引用本文： | 李娟娟,张金艺,张秉煜,周荣俊,唐夏. 蓝牙4.0标准规范下的模糊指纹定位算法[J]. 上海大学学报(自然科学版), 2013, 19(2): 126-131. DOI: 10.3969/j.issn.1007-2861.2013.02.004 |
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| 作者姓名： | 李娟娟 张金艺 张秉煜 周荣俊 唐夏 |
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| 作者单位： | 1. 上海大学特种光纤与光接入网省部共建重点实验室, 上海200072; 2. 上海大学微电子研究与开发中心, 上海200072;3. 上海大学新型显示与系统应用重点实验室, 上海200072 |
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| 基金项目： | 上海市科委基金重点资助项目(08706201000, 08700741000); 上海市教委重点学科建设资助项目(J50104) |
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| 摘 要： | 蓝牙技术的普及以及蓝牙4.0标准规范的提出, 使得利用蓝牙技术实现室内定位具有极其广阔的应用前景.把模糊理论应用于蓝牙室内定位系统, 提出一种模糊指纹定位算法. 基于该算法的定位过程分为离线和在线两个阶段: 离线阶段建立模糊指纹库; 在线阶段对手机客户端进行实时模糊决策定位. 仿真实验结果表明, 该算法的平均定位误差为1.36 m, 相比于传统的指纹标定法, 其定位精度提高约49%, 而计算量缩减至原来的1/c, 其中c为模糊聚类类别数.
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| 关 键 词： | 蓝牙4.0标准规范 模糊理论 实时 室内定位 位置指纹 |
| 收稿时间： | 2012-04-28 |
Fuzzy Fingerprint Location for Bluetooth Specification Version 4.0 |
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| LI Juan-juan,ZHANG Jin-yi,ZHANG Bing-yu,ZHOU Rong-jun,TANG Xia. Fuzzy Fingerprint Location for Bluetooth Specification Version 4.0[J]. Journal of Shanghai University(Natural Science), 2013, 19(2): 126-131. DOI: 10.3969/j.issn.1007-2861.2013.02.004 |
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| Authors: | LI Juan-juan ZHANG Jin-yi ZHANG Bing-yu ZHOU Rong-jun TANG Xia |
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| Affiliation: | 1. Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200072, China;2. Microelectronic Research and Development Center, Shanghai University, Shanghai 200072, China;3. Key Laboratory of Advanced Displays and System Application, Shanghai University, Shanghai 200072, China |
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| Abstract: | Popularity of Bluetooth technology and the proposition of Bluetooth Specification Version 4.0 make indoor location have a broad application prospect. The fuzzy theory is applied in indoor location based on Bluetooth, and a fuzzy fingerprint location algorithm is proposed. The location process is divided into two parts: off-line and on-line. A fuzzy fingerprint database is established in the off-line stage, and real-time location of cell phone clients is realized in the on-line stage. Simulation results show that the average location error is 1.36 m. Compared with traditional fingerprint calibration method, location precision is improved by 49% and computation complexity is reduced to 1/c where c is the category number of fuzzy clustering. |
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| Keywords: | location fingerprint Bluetooth Specification Version 4.0 fuzzy theory indoor location real-time |
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