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ISPRS Int. J. Geo-Inf. 2018, 7(6), 232; https://doi.org/10.3390/ijgi7060232

A RSSI/PDR-Based Probabilistic Position Selection Algorithm with NLOS Identification for Indoor Localisation

1
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
2
School of Engineering, University of Edinburgh, Edinburgh EH8 9YL, UK
*
Author to whom correspondence should be addressed.
Received: 14 May 2018 / Revised: 11 June 2018 / Accepted: 18 June 2018 / Published: 20 June 2018
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Abstract

In recent years, location-based services have been receiving increasing attention because of their great development prospects. Researchers from all over the world have proposed many solutions for indoor positioning over the past several years. However, owing to the dynamic and complex nature of indoor environments, accurately and efficiently localising targets in indoor environments remains a challenging problem. In this paper, we propose a novel indoor positioning algorithm based on the received signal strength indication and pedestrian dead reckoning. In order to enhance the accuracy and reliability of our proposed probabilistic position selection algorithm in mixed line-of-sight (LOS) and non-line-of-sight (NLOS) environments, a low-complexity identification approach is proposed to identify the change in the channel situation between NLOS and LOS. Numerical experiment results indicate that our proposed algorithm has a higher accuracy and is less impacted by NLOS errors than other conventional methods in mixed LOS and NLOS indoor environments. View Full-Text
Keywords: Bluetooth Low Energy; NLOS identification; PDR; indoor localisation; RSSI Bluetooth Low Energy; NLOS identification; PDR; indoor localisation; RSSI
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Han, K.; Xing, H.; Deng, Z.; Du, Y. A RSSI/PDR-Based Probabilistic Position Selection Algorithm with NLOS Identification for Indoor Localisation. ISPRS Int. J. Geo-Inf. 2018, 7, 232.

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