Telecommunications Science ›› 2016, Vol. 32 ›› Issue (7): 21-26.doi: 10.11959/j.issn.1000-0801.2016186

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PCA clustering algorithm for indoor positioning in WLAN

Mingji YANG,Kaiyi LIU,Dan SHAO   

  1. School of Measure-Control Technology and Communication Engineering,Harbin University of Science and Technology,Harbin 150080,China
  • Online:2016-07-20 Published:2017-04-26

Abstract:

In WLAN indoor location system,aiming at the problem of time-varying characteristic of received signal strength (RSS) which reduces indoor positioning accuracy,a clustering algorithm based on principal component analysis (PCA) albino RSS was put forward.The algorithm firstly treated the RSS with PCA whitening treatment to remove the correlation and improve reliability and rationality of the cluster centers.Then,K-means clustering method was used to cluster the RSS and the clustering accuracy was improved effectively,so as to improve positioning accuracy.Experimental results show that compared with the traditional clustering algorithm without PCA,probability of positioning error within 2 meters has improved 44.8% in positioning accuracy,and the performance of positioning system has been more excellent.

Key words: WLAN, indoor positioning, remove the correlation, PCA, clustering algorithm

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