Exploit Kalman filter to improve fingerprint-based indoor localization

Proceedings of 2011 International Conference on Computer Science and Network Technology, ICCSNT 2011

Volumn 4, Issue , 2011, Pages 2290-2293

  Liu, Donghui ^a   Xiong, Yongping ^a   Ma, Jian ^a  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Fingreprint; indoor positioning; Kalman filter; location; tracking

Indexed keywords

BURNING BUILDINGS; COMPLEX BUILDINGS; FINGERPRINT METHOD; FINGREPRINT; INDOOR ENVIRONMENT; INDOOR LOCALIZATION; INDOOR POSITIONING; INDOOR TRACKING; LOCALIZATION ERRORS; MOBILE USERS; POSITIONING ACCURACY; WIRELESS SIGNALS;

COMPUTER SCIENCE; GLOBAL SYSTEM FOR MOBILE COMMUNICATIONS; KALMAN FILTERS; LOCATION; SURFACE DISCHARGES;

MOBILE COMPUTING;

EID: 84860451155     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCSNT.2011.6182431     Document Type: Conference Paper

References (5)

1. Liang Yuan-cheng, The research and implementation of the WLAN based indoor positioning technologies [D], University of Electronic Science and Technology, pp. 9-27, 2009.
2. Zhang Ming-hua, Zhang Shen-sheng and Cao Jian, Received-Signal-Strength- Based Indoor Location in Wireless LANs[J], Computer Science, 34(6), 2007.
3. Li Hao, Indoor Position Techniques Based on Location Fingerprint [J], ShanXi electronic technology, (5), 2007.
4. Tang Li, Xu Yu-bin, Zhou Mu and Deng Zhi-an, Research on K Nearest Neighbors Algorithm under the indoor WLAN(A), Proceedings of 2009 International Forum on Information Technology and Applications(C), 2009.
5. Greg Welch and Gary Bishop, An Introduction to the Kalman Filter [J], University of North Carolina, TR 95-041, July 24, 2006.