期刊文献+

基于接收信号强度的不同移动终端定位方法研究 被引量:5

Research on RSS( Received Signal Strength) Positioning Method When Mobile Terminals Are Different
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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。 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.
出处 《西北工业大学学报》 EI CAS CSCD 北大核心 2014年第3期481-485,共5页 Journal of Northwestern Polytechnical University
基金 国家自然科学基金(50505039)资助
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 algorithms, antennas, experiments, leastmum likelihood estimation, wireless localceived Signal Strength), RSS Difference,squares approximat!ons, linear regression, MATLAB, maxi- area networks ( WLAN ) location fingerprinting, RSS ( Re- RSALS ( Real-time Self Adaptive Learning Standardization)
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参考文献7

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同被引文献38

  • 1ZHOU M,XU Y B,MA L. Adaptive autocorrelation ap-proach for fingerprint-based distance dependent positio-ning algorithms in WLAN indoor areas [J]. Journal ofNetwork,2011,6(10):1475-1482.
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  • 6JAIN V, TAPASWI S, SHUKLA A. RSS fingerprintsbased distributedsemi-supervised locally linear embed-ding location estimation system for indoorWLAN [J].Wireless Personal Communications,2012(1):1-18.
  • 7徐凤燕,李樑宾,王宗欣.一种新的基于区域划分的距离-损耗模型室内WLAN定位系统[J].电子与信息学报,2008,30(6):1405-1408. 被引量:9
  • 8Mu Zhou Yubin Xu Li Tang.Multilayer ANN indoor location system with area division in WLAN environment[J].Journal of Systems Engineering and Electronics,2010,21(5):914-926. 被引量:4
  • 9归奕红.无线传感器网络HEDSA数据聚合研究[J].计算机工程,2011,37(7):160-162. 被引量:35
  • 10陈友荣,王章权,程菊花,刘耀林.基于最短路径树的优化生存时间路由算法[J].传感技术学报,2012,25(3):406-412. 被引量:14

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