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论文:2014,Vol:32,Issue(3):481-485 |
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引用本文： |
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张维, 李文涛, 王力. 基于接收信号强度的不同移动终端定位方法研究[J]. 西北工业大学 |
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Zhang Wei, Li Wentao, Wang Li. Research on RSS(Received Signal Strength) Positioning Method When Mobile Terminals Are Different[J]. Northwestern polytechnical university |
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| 基于接收信号强度的不同移动终端定位方法研究 |
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| 张维, 李文涛, 王力 |
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| 西北工业大学 现代设计与集成制造技术教育部重点实验室, 陕西 西安 710072 |
| 摘要: |
| 传统的基于接收信号强度的定位算法均假设用于线下训练和实时定位的移动终端不变,而这会严重影响基于位置指纹定位法的准确性。本文提出的接收信号强度差值法(RSSD)和实时自适应学习规范化法(RSALS),用于解决不同WLAN移动终端获取接收信号强度存在差异的问题,并在真实室内WLAN环境下验证了算法的可行性和有效性。实验表明即使在设备不变的情况下RSALS法仍然具有实时校正的作用,可以在一定程度上抵消环境变化对定位精度的影响。 |
| 关键词:
算法
天线
实验
最小二乘法
线性回归
MATLAB
最大似然估计
无线局域网
位置指纹
接收信号强度
接收信号强度差值法
实时自适应学习法
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| Research on RSS(Received Signal Strength) Positioning Method When Mobile Terminals Are Different |
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| Zhang Wei, Li Wentao, Wang Li |
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| The Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University, Xi'an 710072, China |
| Abstract: |
| Traditional positioning algorithms based on RSS reckon on the assumption that the mobile terminals used for off-line training and real-time positioning behave identically;this leads to significantly low localization accuracy. The objective of this paper is to investigate the positioning methods for variance in RSS with different WLAN capa-ble mobile devices. Two positioning algorithms are considered:RSSD (RSS Difference) and RSALS(Real-time Self Adaptive Learning Standardization). And also, this paper presents an experiment made in a real indoor WLAN en-vironment and the results and their analysis verify the feasibility and validity of the proposed algorithms. The experi-mental results and their analysis indicate preliminarily that RSALS and RSSD are still effective without mobile de-vice diversity; the results can be explained as being due to partial offset of the positioning accuracy impact of the environmental change. |
| Key words:
algorithms
antennas
experiments
least squares approximations
linear regression
MATLAB
maximum likelihood estimation
wireless local area networks(WLAN)
location fingerprinting
RSS (Received Signal Strength)
RSS Difference
RSALS(Real-time Self Adaptive Learning Standardization)
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| 收稿日期: 2013-10-22
修回日期:
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| DOI: |
| 基金项目: 国家自然科学基金(50505039)资助 |
| 通讯作者:
Email： |
| 作者简介: 张维(1970-),西北工业大学副教授,主要从事数字化制造与物联制造技术研究。
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| 相关功能 |
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| 作者相关文章 |
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| 张维 在本刊中的所有文章 |
| 李文涛 在本刊中的所有文章 |
| 王力 在本刊中的所有文章 |
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参考文献: |
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[1] Park J, Curtis D, Teller S, et al. Implications of Device Diversity for Organic Localization[C]//INFOCOM, Proceedings IEEE, 2011: 3182-3190
[2] Lui G, Gallagher T, Li B, et al. Differences in RSSI Readings Made by Different Wi-Fi Chipsets: A Limitation of WLAN Localization[C]//Localization and GNSS, International Conference IEEE, 2011: 53-57
[3] Fang S H, Wang C H, Chiou S M, et al. Calibration-Free Approaches for Robust Wi-Fi Positioning against Device Diversity: A Performance Comparison[C]//Vehicular Technology Conference IEEE 75th, 2012: 1-5
[4] Kjargaard M B, Munk C V. Hyperbolic Location Fingerprinting: A Calibration-Free Solution for Handling Differences in Signal Strength[C]//Pervasive Computing and Communications, 2008: 110-116
[5] Haeberlen A, Flannery E, Ladd A M, et al. Practical Robust Localization over Large-Scale 802. 11 Wireless Networks[C]//Proceedings of the 10th Annual International Conference on Mobile Computing and Networking, Philadelphia, 2004: 70-84
[6] Tsui A W, Chuang Y H, Chu H H. Unsupervised Learning for Solving RSS Hardware Variance Problem in WiFi Localization [J]. Mobile Networks and Applications, 2009, 14(5): 677-691
[7] Youssef M, Agrawala A. The Horus Location Determination System[J]. Wireless Networks, 2008, 14: 357-374 |
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