A Structure Landmark-Based Radio Signal Mapping Approach for Sustainable Indoor Localization

Tao Liu, Xing Zhang, Huan Zhang, Nadeem Tahir and Zhixiang Fang
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Tao Liu: College of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450002, China
Xing Zhang: Guangdong Key Laboratory of Urban Informatics, the School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
Huan Zhang: Key Laboratory of New Materials and Facilities for Rural Renewable Energy (MOA of China), Henan Agricultural University, Zhengzhou 450002, China
Nadeem Tahir: Key Laboratory of New Materials and Facilities for Rural Renewable Energy (MOA of China), Henan Agricultural University, Zhengzhou 450002, China
Zhixiang Fang: State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430072, China

Sustainability, 2021, vol. 13, issue 3, 1-18

Abstract: Low cost and high reproducible is a key issue for sustainable location-based services. Currently, Wi-Fi fingerprinting based indoor positioning technology has been widely used in various applications due to the advantage of existing wireless network infrastructures and high positioning accuracy. However, the collection and construction of signal radio map (a basis for Wi-Fi fingerprinting-based localization) is a labor-intensive and time-cost work, which limit their practical and sustainable use. In this study, an indoor signal mapping approach is proposed, which extracts fingerprints from unknown signal mapping routes to construct the radio map. This approach employs special indoor spatial structures (termed as structure landmarks) to estimate the location of fingerprints extracted from mapping routes. A learning-based classification model is designed to recognize the structure landmarks along a mapping route based on visual and inertial data. A landmark-based map matching algorithm is also developed to attach the recognized landmarks to a map and to recover the location of the mapping route without knowing its initial location. Experiment results showed that the accuracy of landmark recognition model is higher than 90%. The average matching accuracy and location error of signal mapping routes is 96% and 1.2 m, respectively. By using the constructed signal radio map, the indoor localization error of two algorithms can reach an accuracy of 1.6 m.

Keywords: indoor localization; fingerprinting; structure landmark (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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