Indoor localization method based on RTT and AOA using coordinates clustering

Authors:
M. Dakkak;A. Nakib;B. Daachi;P. Siarry;J. Lemoine
Affiliations:
Université Paris-Est Créteil, Laboratoire Images, Signaux et Systèmes Intelligents (LISSI, E.A. 3956), 61 Avenue du Général De Gaulle, 94010 Créteil, France;Université Paris-Est Créteil, Laboratoire Images, Signaux et Systèmes Intelligents (LISSI, E.A. 3956), 61 Avenue du Général De Gaulle, 94010 Créteil, France;Université Paris-Est Créteil, Laboratoire Images, Signaux et Systèmes Intelligents (LISSI, E.A. 3956), 61 Avenue du Général De Gaulle, 94010 Créteil, France;Université Paris-Est Créteil, Laboratoire Images, Signaux et Systèmes Intelligents (LISSI, E.A. 3956), 61 Avenue du Général De Gaulle, 94010 Créteil, France;Université Paris-Est Créteil, Laboratoire Images, Signaux et Systèmes Intelligents (LISSI, E.A. 3956), 61 Avenue du Général De Gaulle, 94010 Créteil, France
Venue:
Computer Networks: The International Journal of Computer and Telecommunications Networking
Year:
2011

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Abstract

This paper presents a new hybrid indoor localization method using a coordinate clustering technique. This method exploits two parameters, round-trip time (RTT) and angle of arrival (AOA). The advantage of using RTT measurement is to avoid time synchronization between base stations while the coordinate clustering technique helps restrict the localization process by reducing the number of observations at each coordinate level. On the other hand, no prior mitigation technique is applied if an error occurs in a multipath environment as a result of Non Line Of Sight (NLOS). Based on the results of several experiments, indoor location estimation has been proved to be more accurate in two dimensional (2D) as well as in three dimensional (3D) simulated environments.