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    陈永乐, 朱红松, 孙利民. 一种抗多径和阴影的视距指纹定位算法[J]. 计算机研究与发展, 2013, 50(3): 524-531.
    引用本文: 陈永乐, 朱红松, 孙利民. 一种抗多径和阴影的视距指纹定位算法[J]. 计算机研究与发展, 2013, 50(3): 524-531.
    Chen Yongle, Zhu Hongsong, Sun Limin. A Line of Sight Fingerprint Localization Algorithm Resisting Multipath and Shadow[J]. Journal of Computer Research and Development, 2013, 50(3): 524-531.
    Citation: Chen Yongle, Zhu Hongsong, Sun Limin. A Line of Sight Fingerprint Localization Algorithm Resisting Multipath and Shadow[J]. Journal of Computer Research and Development, 2013, 50(3): 524-531.

    一种抗多径和阴影的视距指纹定位算法

    A Line of Sight Fingerprint Localization Algorithm Resisting Multipath and Shadow

    • 摘要: 针对指纹定位算法在实际应用中普遍面临的由人身遮挡造成的多径和阴影干扰问题,通过实验深入分析人身遮挡对指纹算法中信号强度变化的影响,发现利用视距指纹代替原始指纹可以彻底避免阴影的出现,同时也能有效减少多径的影响,在此基础上提出了一种双定位节点的视距指纹定位算法(LoSF).针对视距指纹中存在的异常,LoSF算法还设计了相应的误差处理算法排除视距指纹中的误差数据.通过与现有算法的比较,LoSF算法性能达到了中位数误差2m的精确度,远高于基于原始指纹的RADAR算法所得到的6m精度,也要比带有朝向指纹的COMPASS算法获得的4.2m精度提高一倍之多.

       

      Abstract: Indoor localization utilizing wireless technology is becoming an eager interest of research community in recent years. To provide location aware service, obtaining the position of a user accurately is important. The fingerprint localization based on received signal strength (RSS), is a radio map of the area by measuring the power present in a received radio signal, which don’t require the additional hardware cost. However, utilizing RSS for localization has a number of limitations. For example, the fingerprint localization algorithm generally faces the multipath and shadow interference caused by the physical blocking in the practical application. This paper analyzes how the physical blocking to change the signal strength in fingerprint algorithm, and finds that the line of sight(LoS) fingerprint instead of the original fingerprint can avoid the emergency of shadow and reduce the multipath influence. Based on above analysis, we propose a line of sight fingerprint-based localization algorithm (LoSF). Since the line of sight fingerprint has the abnormal values, we design an error processing algorithm to eliminate errors in the fingerprint data. Compared with the existing algorithms, the performance of LoSF algorithm achieves a median error of 2m, much less than the 6m of RADAR algorithm based on the original fingerprint, and less than the half of the COMPASS algorithm with 4.2m precision.

       

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