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Sensors 2017, 17(6), 1272; doi:10.3390/s17061272

A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications

1
College of Automation, Harbin Engineering University, Harbin 150001, China
2
Department of Geomatics, University of Calgary, Calgary, AB T2N 1N4, Canada
3
Infrastructure Engineering, University of Melbourne, Melbourne, VIC 3010, Australia
*
Author to whom correspondence should be addressed.
Academic Editors: Jesús Ureña, Álvaro Hernández and Juan Jesús García Domínguez
Received: 7 April 2017 / Revised: 24 May 2017 / Accepted: 30 May 2017 / Published: 2 June 2017

Abstract

In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service. View Full-Text
Keywords: non-holonomic constraints; map matching; map aiding; auxiliary value particle filter; indoor location based service system; cascade structure; non-holonomic constraints inertial navigation system (INS); Wi-Fi fingerprinting-aided navigation non-holonomic constraints; map matching; map aiding; auxiliary value particle filter; indoor location based service system; cascade structure; non-holonomic constraints inertial navigation system (INS); Wi-Fi fingerprinting-aided navigation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Yu, C.; Lan, H.; Gu, F.; Yu, F.; El-Sheimy, N. A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications. Sensors 2017, 17, 1272.

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