Indoor positioning technology based on powerline and location fingerprint

被引：0

作者：

He, Jian ^{[1
]}

Wan, Zhi-Jiang ^{[1
]}

Liu, Jin-Wei ^{[2
]}

机构：

[1] School of Software Engineering, Beijing University of Technology, Beijing

[2] Information Center, Beijing University of Technology, Beijing

来源：

Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2014年 / 36卷 / 12期

关键词：

(KNN); Indoor positioning; K-Nearest Neighbor; Location fingerprint; Naive Bayes classification algorithm;

D O I：

10.3724/SP.J.1146.2013.02022

中图分类号：

学科分类号：

摘要：

The power line being indispensable under indoor environment is firstly introduced to be as the antenna, which wideband high-frequency signals are injected into it to obtain the location fingerprint so as to achieve precise indoor positioning. Firstly, the realization technology about the injection of the wideband high-frequency signal analysis is proposed, and the construction method of the indoor location fingerprint is deeply described. Meanwhile, the indoor positioning technology based on the naive Bias classification algorithm is discussed at detail. Finally, the experimental analysis shows that the positioning technology based on naive Bayes classification algorithm has higher positioning accuracy and better adaptive ability of time migration than the positioning technology based on K-Nearest Neighbor (KNN) classification algorithm, in the case of multiple training samples. ©, 2014, Science Press. All right reserved.

引用

页码：2902 / 2908

页数：6

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