Title: Modelling ranging error of indoor TOA-based position system based on receive signal strength

Authors: Jie He; Qin Wang; Qianxiong Zhang; Yanwei Yu; Bingfeng Liu

Addresses: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 10083, China ' School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 10083, China ' School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 10083, China ' School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 10083, China ' School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 10083, China

Abstract: For Time of Arrival (TOA) based indoor position system, the localisation accuracy is significantly affected by the ranging error caused by the severe multipath condition. This paper presents a receive signal strength index (RSSI) based indoor TOA ranging error model, which can be used to estimate the interval of ranging error. In this model, TOA is divided into four classes according to the RSSI of the received data and the error interval of each class can be obtained by analysis and measurement. We described the derivation of the model and then verified it by field testing with commercial available TOA-based localisation system in two typical office environments. Based on the model, we presented a ranging error classification (REC) based indoor TOA localisation algorithm. Result of simulation and field testing shows that the REC algorithm has significantly improved localisation accuracy in the typical indoor environments, comparing with the traditional localisation algorithms.

Keywords: TOA; time of arrival; ranging error models; indoor location systems; IPS; indoor positioning systems; RTLS; modelling; receive signal strength; RSS; localisation accuracy; ranging error classification.

DOI: 10.1504/IJSNET.2013.055005

International Journal of Sensor Networks, 2013 Vol.13 No.3, pp.162 - 172

Published online: 21 Jun 2013 *

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