Leveraging existing WLAN infrastructure for wireless indoor positioning based on fingerprinting and clustering technique

Abstract

The expansion of Wireless Local Area Networks (WLAN) especially the advances in localization based technologies has generated a growing interest in an indoor Wireless Positioning Systems (WPS) based on WLAN infrastructure. This paper presents the preliminary study on two indoor positioning techniques, known as fingerprinting and clustering technique by leveraging the existing Wireless Local Area Network (WLAN) infrastructure in an area with approximately 95% indoor coverage. Initial results indicate that both the clustering and fingerprinting technique able to perform indoor localization. Several enhancement strategies are also presented in order to enhance the accuracy and improve the selection criteria for both clustering and fingerprinting method.