| 基于阈值分类及信号强度加权的室内定位算法 |
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| 引用本文： | 杨小亮,叶阿勇,凌远景. 基于阈值分类及信号强度加权的室内定位算法[J]. 计算机应用, 2013, 33(10): 2711-2714 |
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| 作者姓名： | 杨小亮 叶阿勇 凌远景 |
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| 作者单位： | 福建师范大学 数学与计算机科学学院,福州 350007 |
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| 基金项目： | 国家自然科学基金资助项目，福建省教育厅产学研项目，福建省战略性新兴产业技术开发项目 |
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| 摘 要： | 为了减小室内复杂环境下接收信号强度值（RSSI）波动和个别信标节点被干扰对定位精度的影响，提出一种基于阈值分类及信号强度加权的室内定位算法。先根据室内环境的路径损耗特征，对各参考点进行分类并分别确定其匹配阈值，再将接收信号强度作为参考权重进行加权定位,最终得到更为精确的节点位置。实验表明，该算法能减小RSSI随机抖动引起的误差，有效地削弱个别信标节点被干扰的影响，提高定位精度。
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| 关 键 词： | 室内定位 无线网络 接收信号强度值 阈值分类 信号强度加权 |
| 收稿时间： | 2013-04-07 |
| 修稿时间： | 2013-05-20 |
Indoor localization algorithm based on threshold classification and signal strength weighting |
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| YANG Xiaoliang , YE Ayong , LING Yuanjing. Indoor localization algorithm based on threshold classification and signal strength weighting[J]. Journal of Computer Applications, 2013, 33(10): 2711-2714 |
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| Authors: | YANG Xiaoliang YE Ayong LING Yuanjing |
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| Affiliation: | School of Mathematics and Computer Science, Fujian Normal University,Fuzhou Fujian 350007, China |
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| Abstract: | In order to eliminate the influence caused by fluctuation of Received Signal Strength Indicator (RSSI) and unreliability of individual beacon nodes in complex indoor environment, an indoor localization algorithm based on threshold classification and signal strength weighting was proposed. First, the reference points were classified and corresponding thresholds were determined according to the characteristics of indoor path loss, then the received signal strength was used as reference weight to locate. The experimental results show that this algorithm can effectively reduce the error caused by RSSI random jitter, weaken the influence of individual beacon nodes which are disturbed, and improve localization accuracy. |
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| Keywords: | indoor localization wireless network Received Signal Strength Indicator (RSSI) threshold classification signal strength weighting |
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