A Bayesian Density Model Based Radio Signal Fingerprinting Positioning Method for Enhanced Usability.

Li, Zheng; Liu, Jingbin; Yang, Fan; Niu, Xiaoguang; Li, Leilei; Wang, Zemin; Chen, Ruizhi

Li, Zheng; Liu, Jingbin; Yang, Fan; Niu, Xiaoguang; Li, Leilei; Wang, Zemin; Chen, Ruizhi.

Afiliação

Li Z; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China. 2016206440005@whu.edu.cn.
Liu J; Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China. 2016206440005@whu.edu.cn.
Yang F; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China. jingbin.liu@whu.edu.cn.
Niu X; Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China. jingbin.liu@whu.edu.cn.
Li L; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China. fanyang1990@foxmail.com.
Wang Z; Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China. fanyang1990@foxmail.com.
Chen R; Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China. xgniu@whu.edu.cn.

Sensors (Basel) ; 18(11)2018 Nov 21.

Article em En | MEDLINE | ID: mdl-30469351

Palavras-chave

Bayesian density model; fingerprinting positioning; indoor positioning; received signal strength indication (RSSI)

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China País de publicação: Suíça

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