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Micromachines 2016, 7(11), 197; doi:10.3390/mi7110197

A Fuzzy Adaptive Tightly-Coupled Integration Method for Mobile Target Localization Using SINS/WSN

1
School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China
2
College of Internet of Things Engineering, Hohai University, Changzhou 213022, Jiangsu, China
*
Author to whom correspondence should be addressed.
Academic Editor: Stefano Mariani
Received: 21 April 2016 / Revised: 10 October 2016 / Accepted: 20 October 2016 / Published: 2 November 2016
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Abstract

In recent years, mobile target localization for enclosed environments has been a growing interest. In this paper, we have proposed a fuzzy adaptive tightly-coupled integration (FATCI) method for positioning and tracking applications using strapdown inertial navigation system (SINS) and wireless sensor network (WSN). The wireless signal outage and severe multipath propagation of WSN often influence the accuracy of measured distance and lead to difficulties with the WSN positioning. Note also that the SINS are known for their drifted error over time. Using as a base the well-known loosely-coupled integration method, we have built a tightly-coupled integrated positioning system for SINS/WSN based on the measured distances between anchor nodes and mobile node. The measured distance value of WSN is corrected with a least squares regression (LSR) algorithm, with the aim of decreasing the systematic error for measured distance. Additionally, the statistical covariance of measured distance value is used to adjust the observation covariance matrix of a Kalman filter using a fuzzy inference system (FIS), based on the statistical characteristics. Then the tightly-coupled integration model can adaptively adjust the confidence level for measurement according to the different measured accuracies of distance measurements. Hence the FATCI system is achieved using SINS/WSN. This innovative approach is verified in real scenarios. Experimental results show that the proposed positioning system has better accuracy and stability compared with the loosely-coupled and traditional tightly-coupled integration model for WSN short-term failure or normal conditions. View Full-Text
Keywords: wireless sensor network (WSN); strapdown inertial navigation system (SINS); mobile target; integrated positioning; tightly-coupled integration; fuzzy adaptive; Kalman filter wireless sensor network (WSN); strapdown inertial navigation system (SINS); mobile target; integrated positioning; tightly-coupled integration; fuzzy adaptive; Kalman filter
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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

Li, W.; Yang, H.; Fan, M.; Luo, C.; Zhang, J.; Si, Z. A Fuzzy Adaptive Tightly-Coupled Integration Method for Mobile Target Localization Using SINS/WSN. Micromachines 2016, 7, 197.

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