Indoor INS/UWB-based Human Localization With Missing Data Utilizing Predictive UFIR Filtering

Yuan Xu; Choon Ki Ahn; Yuriy S. Shmaliy; Xiyuan Chen; Lili Bu

doi:10.1109/JAS.2019.1911570

Volume 6 Issue 4

Jul. 2019

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 15.3, Top 1 (SCI Q1)

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2019 > 6(4): 952-960

Yuan Xu, Choon Ki Ahn, Yuriy S. Shmaliy, Xiyuan Chen and Lili Bu, "Indoor INS/UWB-based Human Localization With Missing Data Utilizing Predictive UFIR Filtering," IEEE/CAA J. Autom. Sinica, vol. 6, no. 4, pp. 952-960, July 2019. doi: 10.1109/JAS.2019.1911570

Citation:

Yuan Xu, Choon Ki Ahn, Yuriy S. Shmaliy, Xiyuan Chen and Lili Bu, "Indoor INS/UWB-based Human Localization With Missing Data Utilizing Predictive UFIR Filtering," IEEE/CAA J. Autom. Sinica, vol. 6, no. 4, pp. 952-960, July 2019. doi: 10.1109/JAS.2019.1911570

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Indoor INS/UWB-based Human Localization With Missing Data Utilizing Predictive UFIR Filtering

doi: 10.1109/JAS.2019.1911570

Funds: This work was supported in part by the National Natural Science Foundation of China (61803175), in part by the Project of Shandong Provincial Natural Science Foundation (ZR2018LF010)

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Author Bio:
Yuan Xu (M’16) is a Lecturer of the School of Electrical Engineering at University of Jinan since 2014. He received the B.S. degree in automation from Qilu University of Technology in 2007, and the M.S. degree in detection technology and automation device from Qilu University of Technology in 2010. He received the Ph.D. degree in instrumentation science and technology from Southeast University in 2014. His research interests include integrated navigation and robust filtering

Choon Ki Ahn (M’06–SM’12) received the B.S. and M.S. degrees in the School of Electrical Engineering from Korea University, Seoul, Korea, in 2000 and 2002, respectively. He received the Ph.D. degree at the School of Electrical Engineering and Computer Science from Seoul National University, Seoul, Korea, in 2006. He was a Senior Research Engineer, Samsung Electronics, Suwon, Korea; a Professor with the Department of Mechanical and Automotive Engineering, Seoul National University of Science and Technology, Seoul, Korea. He is currently a Crimson Professor of Excellence with the College of Engineering and a Full Professor with the School of Electrical Engineering, Korea University, Seoul, Korea. He was the recipient of the Early Career Research Award and Excellent Research Achievement Award of Korea University in 2015 and 2016, respectively. He was awarded the Medal for “Top 100 Engineers” 2010 by IBC, Cambridge, England. In 2012, his EPJE paper was ranked #1 in the TOP 20 Articles in the field of neural networks by BioMedLib. In 2013, his two papers were selected as “5 Key Papers” and “5 Popular Papers” in Nonlinear Dynamics, Springer. In 2015, his paper was ranked #6 in the “Top 50 Most Popular Articles” for IEEE Transactions on Automatic Control. In 2017 and 2018, his papers were ranked in Most Cited Articles published in the last 5 years for IEEE Transactions on Circuits and Systems I: Regular Papers and IEEE Transactions on Circuits and Systems II: Express Briefs. In 2016, he was ranked #1 in Electrical/Electronic Engineering and #2 in entire areas of Engineering among Korean young professors based on paper quality. In 2017, he received the Presidential Young Scientist Award of Korea. He is a Senior Member of the IEEE. His current research interests include control, filtering, two-dimensional system theory, fuzzy systems, neural networks, and nonlinear dynamics. He has been on the editorial board of international journals, including the IEEE Systems, Man, and Cybernetics Magazine; IEEE Transactions on Neural Networks and Learning Systems; IEEE Transactions on Fuzzy Systems; IEEE Transactions on Systems, Man, and Cybernetics: Systems; IEEE Transactions on Automation Science and Engineering; IEEE Systems Journal; Nonlinear Dynamics; Aerospace Science and Technology; Artificial Intelligence Review; and other leading journals

Yuriy S. Shmaliy (M’96–SM’00–F’11) received the B.S., M.S., and Ph.D. degrees in 1974, 1976 and 1982, respectively, from the Kharkiv Aviation Institute, Ukraine, all in electrical engineering. He serves as Full Professor beginning in 1986. In 1992 he received the D.Sc. degree from the Kharkiv Railroad Institute. Since 1985 to 1999, he had been with the Kharkiv Military University. In 1992, he founded the Scientific Center Sichron where he was a director by 2002. Since 1999, he has been with the Universidad de Guanajuato of Mexico and headed the Department of Electronics Engineering in this University from 2012 to 2015. In 2015-2016, he has been a visiting researcher in City University London and, in 2015, 2017–2019, in TELECOM SudParis. Dr. Shmaliy has 450 Journal and Conference papers and holds 81 patents. His books Continuous-Time Signals (2006) and Continuous-Time Systems (2007) were published by Springer. His book GPS-Based Optimal FIR Filtering of Clock Models (2009) was published by Nova Science Publ., New York. He also edited a book Probability: Interpretation, Theory and Applications published by Nova Science Publ., New York, in 2012 and contributed to several books with invited chapters. He was rewarded a title, Honorary Radio Engineer of the USSR, in 1991. He was listed in Outstanding People of the 20th Century, Cambridge, England, in 1999 and has received the Royal Academy of Engineering Newton Research Collaboration Program Award in 2015. He is currently an Editorial Board Member in several Journals. He was research invited many times to give tutorial, seminar, and plenary lectures. His current research interests include optimal estimation, statistical signal processing, and stochastic system theory

Xiyuan Chen (M’08–SM’13) received the B.S. degree in mechanical engineering from Lanzhou University of Technology, China, in 1990. He received the MSc degree in mechanical engineering from Hefei University of Technology, China, in 1995. He received the Ph.D. degree in precision instrument and mechanical engineering from Southeast University, China, in 1998. He is currently a Professor of School of Instrument Science and Engineering, Southeast University, China. His research interests include inertial navigation and integrated measurement

Lili Bu received the B.S. degree in automation from the University of Jinan in 2016, and now is a postgraduate student, majoring in control engineering at the University of Jinan. Her main research interest is indoor pedestrian positioning
Corresponding author: Y. Xu and L. L. Bu are with the School of Electrical Engineering, University of Jinan, Jinan 250022, China (e-mail: xy_abric@126.com; bu18366105277@163.com)
Received Date: 2019-02-13
Revised Date: 2019-04-09
Accepted Date: 2019-05-14

Available Online: 2019-06-04

Abstract

Abstract

A combined algorithm for the loosely fused ultra wide band (UWB) and inertial navigation system (INS)-based measurements is designed under the indoor human navigation conditions with missing data. The scheme proposed fuses the INS- and UWB-derived positions via a data fusion filter. Since the UWB signal is prone to drift in indoor environments and its outage highly affects the integrated scheme reliability, we also consider the missing data problem in UWB measurements. To overcome this problem, the loosely-coupled INS/UWB-integrated scheme is augmented with a prediction option based on the predictive unbiased finite impulse response (UFIR) fusion filter. We show experimentally that, the standard UFIR fusion filter has higher robustness than the Kalman filter. It is also shown that the predictive UFIR fusion filter is able to produce an acceptable navigation accuracy under temporary missing UWB-data.
- Indoor human navigation,
- INS/UWB model,
- prediction,
- unbiased FIR filter

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References(26)

References

[1]	J. Yang, J. Ma, X. Liu, L. Qi, Z. Wang, Y. Zhuang, and L. Shi, " A height constrained adaptive Kalman filtering based on climbing motion model for GNSS positioning,” IEEE Sensors Journal, vol. 17, no. 21, pp. 7105–7113, Nov. 2017. doi: 10.1109/JSEN.2017.2752751
[2]	A. Sharma, A. T. Hoang, and M. S. Reynolds, " Long range battery-free UHF RFID with a single wire transmission line,” IEEE Sensors Journal, vol. 17, no. 17, pp. 5687–5693, Sep. 2017. doi: 10.1109/JSEN.2017.2727494
[3]	J. J. Pomarico-Franquiz and Y. S. Shmaliy, " Accurate self-localization in RFID tag information grids using FIR filtering,” IEEE Trans. Industrial Informatics, vol. 10, no. 2, pp. 1317–1326, May 2014. doi: 10.1109/TII.2014.2310952
[4]	N. Decarli, F. Guidi, and D. Dardari, " Passive UWB RFID for tag localization: Architectures and design,” IEEE Sensors Journal, vol. 16, no. 5, pp. 1385–1397, Mar. 2016. doi: 10.1109/JSEN.2015.2497373
[5]	Y. Xu, Y. S. Shmaliy, Y. Li, and X. Chen, " UWB-based indoor human localization with time-delayed data using EFIR filtering,” IEEE Access, vol. 5, pp. 16676–16683, Aug. 2018.
[6]	Y. Zhuang, Y. Li, L. Qi, H. Lan, J. Yang, and N. El-Sheimy, " A twofilter integration of MEMS sensors and WiFi fingerprinting for indoor positioning,” IEEE Sensors Journal, vol. 16, no. 13, pp. 5125–5126, Jul. 2016. doi: 10.1109/JSEN.2016.2567224
[7]	C. Huang, Z. Liao, and L. Zhao, " Synergism of INS and PDR in selfcontained pedestrian tracking with a miniature sensor module,” IEEE Sensors Journal, vol. 10, no. 8, pp. 1349–1359, May 2010. doi: 10.1109/JSEN.2010.2044238
[8]	H. Cao, Y. Zhang, Z. Han, X. Shao, J. Gao, K. Huang, Y. Shi, J. Tang, J. Liu, and C. Shen, " Pole-Zero-Temperature compensation circuit design and experiment for dual-mass MEMS gyroscope bandwidth expansion,” IEEE/ASME Trans. Mechatronics, 2019. doi: 10.1109/TMECH.2019.2898098
[9]	Y. Xu and X. Chen, " Online cubature Kalman filter Rauch-Tung-Striebel smoothing for indoor inertial navigation system/ultrawideband integrated pedestrian navigation,” in Proc. Institution of Mechanical Engineers, Part I, J. Systems and Control Engineering, no. 232, pp. 390–398, May 2018.
[10]	H. Nourmohammadi and J. Keighobadi, " Decentralized INS/GNSS system with MEMS-grade inertial sensors using QR-factorized CKF,” IEEE Sensors Journal, vol. 17, no. 11, pp. 3278–3287, Jun. 2017. doi: 10.1109/JSEN.2017.2693246
[11]	L. Bu, Y. Zhang, and Y. Xu, " Indoor pedestrian tracking by combining recent INS and UWB measurements,” in Proc. Int. Conf. Advanced Mechatronic Systems, 2017, pp. 244-248.
[12]	Y. Zhuang, H. Lan, Y. Li, and N. Elsheimy, " PDR/INS/WiFi integration based on handheld devices for indoor pedestrian navigation,” Micromachines, vol. 6, no. 6, pp. 793–812, Jun. 2015. doi: 10.3390/mi6060793
[13]	A. R. Jimnez, F. Seco, J. C. Prieto, and J. Guevara, " Indoor pedestrian navigation using an INS/EKF framework for yaw drift reduction and a foot-mounted IMU,” Positioning Navigation and Communication, 2010, pp. 135–143.
[14]	Y. Li, H. R. Karimi, Q. Zhang, D. Zhao, and Y. Li, " Fault detection for linear discrete time-varying systems subject to random sensor delay: a Riccati equation approach,” IEEE Trans. Circuits and Systems, vol. 65, no. 5, pp. 1707–1716, 2018. doi: 10.1109/TCSI.2017.2763625
[15]	Y. L. Hsu, J. S. Wang, and C. W. Chang, " A wearable inertial pedestrian navigation system with quaternion-based extended Kalman filter for pedestrian localization,” IEEE Sensors Journal, vol. 17, no. 10, pp. 3193–3206, May 2017. doi: 10.1109/JSEN.2017.2679138
[16]	H. Huang, X. Chen, B. Zhang, and J. Wang, " High accuracy navigation information estimation for inertial system using the multi-model EKF fusing adams explicit formula applied to underwater gliders,” ISA Trans., vol. 66, pp. 414–424, 2016.
[17]	S. Zhao, Y. S. Shmaliy, C. K. Ahn, and F. Liu, " Adaptive-horizon iterative UFIR filtering algorithm with applications,” IEEE Trans. Industrial Electronics, vol. 65, no. 8, pp. 6393–6402, Aug. 2017.
[18]	Jazwinski and AndrewH, Stochastic Processes and Filtering Theory. Academic Press, 1970.
[19]	S. Zhao, Y. S. Shmaliy, P. Shi, and C. K. Ahn, " Fusion Kalman/UFIR filter for state estimation with uncertain parameters and noise statistics,” IEEE Trans. Industrial Electronics, vol. 64, no. 4, pp. 3075–3083, Apr. 2017. doi: 10.1109/TIE.2016.2636814
[20]	S. Zhao, Y. S. Shmaliy, C. Ahn, and P. Shi, " Real-time optimal state estimation of multi-DOF industrial systems using FIR filtering,” IEEE Trans. Industrial Informatics, vol. 13, no. 3, pp. 967–975, Aug. 2017. doi: 10.1109/TII.2016.2601071
[21]	C. K. Ahn, S. Zhao, and Y. S. Shmaliy, " Frequency-efficient receding horizon H_∞ FIR filtering in discrete-time state-space,” IEEE Trans. Circuits and Systems I Regular Papers, vol. 64, no. 11, pp. 2945–2953, Jun. 2017. doi: 10.1109/TCSI.2017.2705982
[22]	Y. S. Shmaliy, S. Zhao, and C. K. Ahn, " Unbiased FIR filtering: an iterative alternative to Kalman filtering ignoring noise and initial conditions,” IEEE Control Syst. Mag., vol. 37, no. 5, pp. 70–89, Oct. 2017. doi: 10.1109/MCS.2017.2718830
[23]	Y. Xu, C. K. Ahn, Y. S. Shmaliy, X. Chen, and Y. Li, " Adaptive robust INS/UWB-integrated human tracking using UFIR filter bank,” Measurement, vol. 123, pp. 1–7, Jul. 2018.
[24]	M. Vazquez-Olguin, Y. Shmaliy, C. K. Ahn, and O. Ibarra-Manzano, " Blind robust estimation with missing data for smart sensors using UFIR filtering,” IEEE Sensors Journal, vol. 17, no. 6, pp. 1819–1827, Mar. 2017. doi: 10.1109/JSEN.2017.2654306
[25]	J. M. Pak, C. K. Ahn, Y. S. Shmaliy, and M. T. Lim, " Improving reliability of particle filter-based localization in wireless sensor networks via hybrid Particle/FIR filtering,” IEEE Trans. Industrial Informatics, vol. 11, no. 5, pp. 1089–1098, May 2015. doi: 10.1109/TII.2015.2462771
[26]	Y. S. Shmaliy, F. Lehmann, S. Zhao, and C. K. Ahn, " Comparing robustness of the Kalman, H∞, and UFIR filters,” IEEE Trans. Signal Process., vol. 65, no. 13, pp. 3447–3458, Jul. 2018.

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Indoor INS/UWB-based Human Localization With Missing Data Utilizing Predictive UFIR Filtering

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