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A Frequency Modulation Fingerprint-Based Positioning Algorithm for Indoor Mobile Localization of Photoelectric Modules
Frontiers in Physics ( IF 1.9 ) Pub Date : 2020-11-23 , DOI: 10.3389/fphy.2020.619363
Chi Duan , Lixia Tian , Pengfei Bai , Bao Peng

Optoelectronic modules have a wide range of applications in the field of wireless communication. However, the function of mobile localization has not been realized in optoelectronic modules. In this paper, an indoor positioning algorithm, which was based on frequency modulation (FM) signals, was realized in optoelectronic modules. Firstly, FM monitoring receiver DB4004 was used to collect FM signals; Secondly, FM signals were preprocessed and analyzed to build a FM dataset. Finally, weighted centroid k-nearest neighbors (WC-KNN) precise positioning algorithm was proposed to obtain the position information of the photoelectric module. Experimental results showed that the median location error of the WC-KNN algorithm can reach 0.8 m and additional hardware equipment was not required. The research results provided the feasibility for the practical application of equipment based on optoelectronic devices in various fields.



中文翻译:

基于频率调制指纹的光电模块室内移动定位算法

光电模块在无线通信领域具有广泛的应用。但是,移动定位的功能尚未在光电模块中实现。本文在光电模块中实现了基于调频(FM)信号的室内定位算法。首先,使用调频监视接收机DB4004采集调频信号。其次,对FM信号进行预处理和分析以建立FM数据集。最后,提出了加权质心近邻(WC-KNN)精确定位算法,以获取光电模块的位置信息。实验结果表明,WC-KNN算法的中值定位误差可达0.8 m,不需要额外的硬件设备。

更新日期:2021-01-25
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