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ABSTRACT
This paper proposes a new method of 3D indoor positioning based on Bluetooth devices. Virtual Received Signal Strength Indicator (RSSI) fingerprint is built on RSSI difference and distance ratio. The concepts and stability of 1D and 2D virtual fingerprints are introduced, and the property of uniqueness for virtual fingerprint is proved. 2D virtual fingerprint is more stable than that of 1D for indoor positioning. Various positioning algorithms, based on virtual fingerprint and one-way ranging, are discussed, such as NN, KNN, Multi-Step and nonlinear optimization, inference and regression. Multi-Step algorithm holds the best performance in time and error. The proposed method utilizes virtual fingerprint and two-way ranging to overcome the four evident shortcomings of the traditional RRSI fingerprint-based methods. Firstly, measured RSSI is calibration-less for different Bluetooth devices and varying battery status. Secondly, virtual fingerprint of training is obtained by computing, not measured point by point in whole 3D indoor environment. Thirdly, 3D indoor positioning method is employed to substitute for the classical 2D positioning methods. Finally, two-way ranging is adopted to take the place of the conventional one-way ranging and improve the positioning precision. The correctness and availability of the proposed method are testified by the simulation and hardware experiments.
Disclosure statement
No potential conflict of interest was reported by the authors .
Additional information
Notes on contributors
Honggui Li
Honggui Li received a B.S. degree in electronic science and technology from Yangzhou University in 1994 and received a Ph.D. degree in mechatronic engineering from Nanjing University of Science and Technology in 1999. He is a senior member of the Chinese Institute of Electronics. He was a visiting scholar and a post-doctoral fellow in Institut Supérieur d’Électronique de Paris in 2016. He is an associate professor of electronic science and technology and a postgraduate supervisor of electronic science and technology at Yangzhou University. He is a reviewer for some international journals and conferences. He is the author of over 30 refereed journals and conference articles. His current research interests include embedded computing, computer vision, and machine learning.
Maria Trocan
Maria Trocan received her M.Eng. in Electrical Engineering and Computer Science from Politehnica University of Bucharest in 2004, the Ph.D. in Signal and Image Processing from Telecom ParisTech in 2007 and the Habilitation to Lead Researches (HDR) from Pierre & Marie Curie University (Paris 6) in 2014. She joined Joost – Netherlands in 2007, where she worked as a research engineer involved in the design and development of video transcoding systems. Since May 2009 she has been an Associate Professor, then became a Professor (2016) at Institut Superieur d’Electronique de Paris (ISEP). She is an Associate Editor for Springer Journal on Signal, Image and Video Processing and Guest Editor for several journals (Analog Integrated Circuits and Signal Processing, IEEE Communications Magazine etc.). Since 2010, she has been an active member of IEEE France and served as counselor for the ISEP IEEE Student Branch, IEEE France Vice-President responsible of Student Activities and IEEE Circuits and Systems Board of Governors member, as Young Professionals representative. Her current research interests focus on image and video analysis and compression and sparse signal representations.
Dimitri Galayko
Dimitri Galayko received the bachelor’s degree from Odessa State Polytechnic University, Ukraine, in 1998, the master’s degree from the Institute of Applied Sciences of Lyon, France, in 1999, and the Ph.D. degree from University Lille in 2002. He made his Ph.D. thesis in the Institute of Microelectronics and Nanotechnologies, Lille, France. His Ph.D. dissertation was on the design of micro-electromechanical silicon filters and resonators for radio-communications. Since 2005 he has been an Associate Professor with the LIP6 research laboratory, Sorbonne University. His research interests include study, modeling, and design of nonlinear integrated circuits for sensor interface and for mixed-signal applications.