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Exploring Fast Fingerprint Construction Algorithm for Unmodulated Visible Light Indoor Localization.
Shi, Chenqi; Niu, Xinyv; Li, Tao; Li, Sen; Huang, Chanjuan; Niu, Qiang.
Affiliation
  • Shi C; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Niu X; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Li T; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Li S; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Huang C; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Niu Q; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
Sensors (Basel) ; 20(24)2020 Dec 17.
Article in En | MEDLINE | ID: mdl-33348777
The study of visible light indoor position has received considerable attention. The visible light indoor position has problems such as deployment difficulty and high cost. In our system, we propose a new fingerprint construction algorithm to simplify visible light indoor position. This method can realize the rapid construction of a visible fingerprint database and prove that the fingerprint database can be used repeatedly in different environments. We proved the theoretical feasibility of this method through theoretical derivation. We carried out extensive experiments in two classic real indoor environments. Experimental results show that reverse fingerprinting can be achieved. In 95% of cases, the positioning accuracy can be guaranteed to be less than 10 cm.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Sensors (Basel) Year: 2020 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Sensors (Basel) Year: 2020 Type: Article Affiliation country: China