Accurate wireless indoor position estimation by using hybrid TDOA/RSS algorithm

Location Determination in an indoor environment is a challenge being faced by wireless industries. The concept of the indoor geolocation was established in order to provide the user's location inside buildings during an emergency where global navigation satellite system (GNSS) services are not available. Keeping public safety in mind, it is important not only to estimate the position, but also to provide a high level of reliability. The paper presents practical results and issues related to the accuracy of an indoor geolocation system, which uses a wideband code division multiple access (WCDMA) signal at a 2.45 GHz carrier frequency. This experiment employs a hybrid Time Difference Of Arrival (TDOA) / Received Signal Strength (RSS) algorithm and a TDOA only algorithm. Practical results indicate that the positioning performance is improved by using the hybrid TDOA/RSS algorithm as compared to the TDOA only algorithm.

[1]  V. S. Abhayawardhana,et al.  Comparison of empirical propagation path loss models for fixed wireless access systems , 2005, 2005 IEEE 61st Vehicular Technology Conference.

[2]  Michel Fattouche,et al.  Time Sum of Arrival Based BLUE for Mobile Target Positioning , 2011 .

[3]  Don J. Torrieri,et al.  Statistical Theory of Passive Location Systems , 1984, IEEE Transactions on Aerospace and Electronic Systems.

[4]  Fadhel M. Ghannouchi,et al.  Handset-Based Positioning System for Injured Fireman Rescue in Wildfire Fighting , 2012, IEEE Systems Journal.

[5]  Wei Ni,et al.  Indoor Location Algorithm Based on the Measurement of the Received Signal Strength , 2006 .

[6]  Zafer Sahinoglu,et al.  The Cramer-Rao bounds of hybrid TOA/RSS and TDOA/RSS location estimation schemes , 2004, IEEE Communications Letters.

[7]  Alfred O. Hero,et al.  Relative location estimation in wireless sensor networks , 2003, IEEE Trans. Signal Process..

[8]  Gordon L. Stüber,et al.  Subscriber location in CDMA cellular networks , 1998 .

[9]  Michel Fattouche,et al.  Novel Wireless Positioning System for OFDM-Based Cellular Networks , 2012, IEEE Systems Journal.

[10]  Li Zheng,et al.  An indoor position estimation method by maximum likelihood algorithm using RSS , 2007, SICE Annual Conference 2007.

[11]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[12]  A.H. Sayed,et al.  Network-based wireless location: challenges faced in developing techniques for accurate wireless location information , 2005, IEEE Signal Processing Magazine.

[13]  Ian Oppermann,et al.  UWB location and tracking for wireless embedded networks , 2006, Signal Process..

[14]  Ali H. Sayed,et al.  Network-based wireless location , 2005 .

[15]  Wang Zong-xin,et al.  Indoor Location Algorithm Based on the Measurement of the Received Signal Strength , 2004 .