J4 ›› 2015, Vol. 42 ›› Issue (6): 81-87.doi: 10.3969/j.issn.1001-2400.2015.06.015

• Original Articles • Previous Articles     Next Articles

Fingerprint optimization method for the indoor localization system

MA Xindi;MA Jianfeng;GAO Sheng   

  1. (School of Computer Science and Technology, Xidian Univ., Xi'an  710071, China)
  • Received:2014-07-10 Online:2015-12-20 Published:2016-01-25
  • Contact: MA Xindi E-mail:xdma1989@163.com

Abstract:

The accuracy of the indoor localization is influenced directly by the quality of the fingerprint. But the indoor localization algorithms in existence are almost conducted based on the original fingerprint which is not optimized. The k-means is introduced to optimize the fingerprint in this paper. And deleting the collected bad-points through the theory of cluster could make the fingerprint more accurate for the indoor localization algorithm. Compared with the indoor localization systems in existence, the result of experiments shows that the optimized fingerprint can increase the accurate of indoor localization with a higher probability.

Key words: smartphone, k-means method, optimize fingerprint, delete bad-point