Bluetooth Indoor Positioning Based on RSSI and Kalman Filter-Reference-Cited by-同舟云学术

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Bluetooth Indoor Positioning Based on RSSI and Kalman Filter

Published:2017-07-25 Issue:3 Volume:96 Page:4115-4130
ISSN:0929-6212
Container-title:Wireless Personal Communications
language:en
Short-container-title:Wireless Pers Commun

Author:

Zhou Cheng,Yuan Jiazheng,Liu Hongzhe,Qiu Jing

Funder

The National Natural Science Foundation of China

Beijing Municipal Natural Science Foundation (CN)

The National Key Technology R&D Pro

Funding Project for Academic Human Resources Development in Beijing Union University

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

http://link.springer.com/article/10.1007/s11277-017-4371-4/fulltext.html

Reference29 articles.

1. Calderoni, L., Maio, D., & Palmieri, P. (2012). Location-aware mobile services for a smart city: Design, implementation and deployment. Journal of Theoretical and Applied Electronic Commerce Research, 7(3), 74–87.

2. Pivato, P. (2012). Analysis and characterization of wireless positioning techniques in indoor environment. Trento: University of Trento.

3. Vahidnia, M. H., Malek, M. R., Mohammadi, N., et al. (2013). A hierarchical signal-space partitioning technique for indoor positioning with WLAN to support location-awareness in mobile map services. Wireless Personal Communications, 69(2), 689–719.

4. Wang, Y., Yang, X., Zhao, Y., et al. (2013). Bluetooth positioning using RSSI and triangulation methods. In Consumer communications and networking conference (CCNC), 2013 IEEE. IEEE, pp. 837–842.

5. Fang, S. H., Wang, C. H., Huang, T. Y., et al. (2012). An enhanced ZigBee indoor positioning system with an ensemble approach. Communications Letters, IEEE, 16(4), 564–567.

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