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Map assisted PDR/Wi-Fi fusion for indoor positioning using smartphone

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  • Control Theory and Applications
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Abstract

In this paper we present a map-assisted pedestrian navigation system for smartphone user which combines map information, IMU-based Pedestrian Dead Reckoning (PDR) and Wi-Fi localization using fingerprinting method. PDR (Pedestrian Dead Reckoning) using smartphone consist with step detection, step length estimation and heading estimation. However, these algorithms have errors caused by various reasons such as step length error at uncertain user, magnetic disturbance in indoor situation and unstable position of smartphone. To increase accuracy of the PDR, Wi-Fi fusion or map matching method has been proposed. However, previous methods could not solve fault matching or creating map in hall area. Especially in hall, pedestrian could make various trajectories that accurate map structures are required. For solving the structure of map database in hall problem and accurate link selection, we propose a Virtual Link (VL) algorithm with a Virtual Track (VT). Furthermore, an Extended Kalman Filter (EKF) is used for estimating pedestrian position and IMU sensor errors. With map information, step length estimation error, heading error at pedestrian dead reckoning and some IMU sensor errors are estimated. Real world experiments are conducted at building, and it shows less than 3m of CEP (Circular Error Probability) after 200m walk.

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Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, ASRI, Seoul National University, Seoul, Korea

    Min Su Lee, Hojin Ju & Chan Gook Park

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  1. Min Su Lee
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  2. Hojin Ju
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  3. Chan Gook Park
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Corresponding author

Correspondence to Min Su Lee.

Additional information

Recommended by Associate Editor Bin Jiang under the direction of Editor Fuchun Sun. This journal was supported by the ICT R&D program of MSIP/IITP. [R0101-15-0168, Development of ODM-interactive Software Technology supporting Live-Virtual Soldier Exercises].

Min Su Lee received his B.S. and Ph.D. in the School of Mechanical and Aerospace Engineering of Seoul National University in 2008. His current research interests include the pedestrian dead reckoning, indoor navigation, context awareness and kinematic based position using multiple wearable sensors.

Hojin Ju is a Ph.D. student in the School of Mechanical and Aerospace Engineering of Seoul National University, Seoul, South Korea. He received his B.S. in Mechanical Engineering from Korea Aerospace University in 2012. His current research interests include the pedestrian dead reckoning, inertial navigation systems, nonlinear filter and pattern recognition.

Chan Gook Park received the B.S., M.S., and Ph.D. in control and instrumentation engineering from Seoul National University, Seoul, Korea, in 1985, 1987, and 1993, respectively. He worked with Prof. Jason L. Speyer on peak seeking control for formation flight at the University of California, Los Angeles (UCLA) as a postdoctoral fellow in 1998. From 1994 to 2003, he was with Kwangwoon University, Seoul, Korea, as an associate professor. In 2003, he joined the faculty of the School of Mechanical and Aerospace Engineering at Seoul National University, Korea, where he is currently a professor. From 2009 to 2010, he was a visiting scholar with the Department of Aerospace Engineering at Georgia Institute of Technology, Atlanta, GA. He served as a chair of IEEE AES Korea Chapter until 2009. His current research topics include advanced filtering techniques, inertial navigation system (INS), GPS/INS integration, MEMS-based pedestrian dead reckoning, and FDIR techniques for satellite systems.

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Lee, M.S., Ju, H. & Park, C.G. Map assisted PDR/Wi-Fi fusion for indoor positioning using smartphone. Int. J. Control Autom. Syst. 15, 627–639 (2017). https://doi.org/10.1007/s12555-015-0342-2

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  • DOI: https://doi.org/10.1007/s12555-015-0342-2

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