Probability Distribution-Aided Indoor Positioning Algorithm Based on Affinity Propagation Clustering

  • Zengshan Tian
  • Xiaomou Tang
  • Mu Zhou
  • Zuohong Tan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 246)


With the rapid development of indoor positioning technology, the fingerprint-based Wireless Local Area Network (WLAN) positioning becomes a new and widely recognized research concern. This paper proposes a probability distribution-aided indoor positioning algorithm based on the affinity propagation clustering. Different from the conventional fingerprint-based positioning algorithms, our algorithm first uses the affinity propagation clustering to minimize the searching space of reference points (RPs). Then, the probability distribution-aided positioning algorithm is utilized to estimate the target’s accurate position. Furthermore, because the affinity propagation clustering can effectively reduce the computation cost for the RP searching which is involved in the probability distribution-aided positioning algorithm, the positioning efficiency of our proposed algorithm can be effectively guaranteed. Experimental results demonstrate that our proposed affinity propagation clustering will significantly improve the performance of the probability distribution-aided positioning algorithm in both the positioning accuracy and real-time ability.


WLAN indoor positioning Fingerprinting Affinity propagation clustering RSS Probability distribution 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Zengshan Tian
    • 1
  • Xiaomou Tang
    • 1
  • Mu Zhou
    • 1
  • Zuohong Tan
    • 1
  1. 1.Chongqing Key Lab of Mobile Communications Technology, School of Communication & Information EngineeringChongqing University of Posts and TelecommunicationsChongqingChina

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