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Improving Human Hand Localization in Indoor Environment by Using Frequency Domain Analysis

Authors: Wipassorn Vinicchayakul, Pichaya Supanakoon, Sathaporn Promwong

Abstract:

A human’s hand localization is revised by using radar cross section (RCS) measurements with a minimum root mean square (RMS) error matching algorithm on a touchless keypad mock-up model. RCS and frequency transfer function measurements are carried out in an indoor environment on the frequency ranged from 3.0 to 11.0 GHz to cover federal communications commission (FCC) standards. The touchless keypad model is tested in two different distances between the hand and the keypad. The initial distance of 19.50 cm is identical to the heights of transmitting (Tx) and receiving (Rx) antennas, while the second distance is 29.50 cm from the keypad. Moreover, the effects of Rx angles relative to the hand of human factor are considered. The RCS input parameters are compared with power loss parameters at each frequency. From the results, the performance of the RCS input parameters with the second distance, 29.50 cm at 3 GHz is better than the others.

Keywords: fingerprint-based localization, minimum root mean square (RMS) error matching algorithm, touchless keypad model, Radar cross section (RCS)

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1111644

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References:


[1] C. Nerguizian, C. Despins and S. Affès, “Geolocation in Mines with an Impulse Response Fingerprinting Technique and Neural Networks,” Journal of Communications, Vol. 5, No. 3, pp. 603-611, March 2006.
[2] A. Toak, N. Kandil, S. Affès and S. Georges, “Neural Networks for Fingerprinting-Based Indoor Localization Using Ultra-Wideband,” Journal of Communications. 01/2009.
[3] L. Zwirello, M. Janson, C. Ascher and U. Schwesinger, “Localization in Industrial Halls via Ultra-Wideband Signals,” 2010 Workshop on Positioning Navigation and Communication, pp. 144–149, Mar. 2010.
[4] M. Stella, M. Russo and D. Begusic, “Location Determination in indoor Environment based on RSS Fingerprinting and Artificial Neural Network,” Telecommunications, 2007, ConTel 2007, 9th International Conference on 13-15 June 2007, pp. 301-306.
[5] M. Zhou, Y. Xu and L. Tang, “Multilayer ANN indoor location system with area division in WLAN environment,” Systems Engineering and Electronics, Journal of, vol. 21, no. 5, pp. 914–926, October 2010.
[6] M.L. Rodrigues, “Fingerprinting-Based Radio Localization in indoor Environment Using Multiple Wireless Technologies” 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications, pp 1203 - 1207.
[7] Z. Sahinoglu, S. Gezici and I. Guvenc, “Ultra-wideband Positioning Systems,” New York: Cambridge University, Inc. 2008.
[8] C. Wu, Z. Yang, Y. Liu, and W. Xi, “WILL: Wireless Indoor Localization without Site Survey,” IEEE Transactions on Parallel and Distributed Systems, Vol. 24, No. 4, April 2013.
[9] H. Liu, H. Darabi, P. Banerjee and J. Liu, “Survey of wireless indoor positioning techniques and systems,” IEEE Transactions on Systems, Man, and Cybernetics Part C, vol. 37, no. 6, pp. 1067–1080, Nov. 2007.
[10] G. Mao and B. Fidan, “Localization Algorithms and Strategies for Wireless Sensor Networks,” New York: Hershey, United States of America, 2009, ch. 3-5, ch. 11.
[11] A. Srikaew. “Computational Intelligence Book,” https://sites.google.com/site/Computationalintelligencebook/download.
[12] L.C.D. Jong, and H.A.J. Herben, "A Tree-Scattering Model for Improved Propagation Prediction in Urban Microcells," IEEE Transactions on Vehicular Technology, vol. 53, no. 2, pp. 503-513, 2004.
[13] C. Lim, J.L. Volakis, K. Sertel, R.W. Kindt and A. Anastasopoulo, "Indoor Propagation models based on rigorous methods for site-specific multipath environment," IEEE Transactions on Antennas and Propagation, vol. 54, no. 6, pp. 1718-1725, 2006.
[14] M. Cheffena, "Physical-Statistical Channel Model for Signal Effect by Moving Human Bodies," EURASIP Journal on Wireless Communications and Networking, 2012:77, pp. 1-13, 2012.
[15] Understanding the FCC Regulations for Low-power, Nonlicensed Transmitters. Office of Engineering and Technology Federal Communications Commission, 1993.
[16] E.F. Knott, J.F. Shaeffer, and M.T. Tuley, “Radar Cross Section,” Artech House, New Jersey. United States of America, 1985, ch. 1-2, ch. 5-6 and ch. 11.
[17] C. Ozdemir, “Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms,” John Wiley & Sons, Inc., Hoboken, New Jersey. Singapore, 2012, ch. 2.
[18] B.R. Mahafza, “Radar Systems Analysis and Design Using MATLAB,” Taylor & Francis Group, LLC, Chapman & Hall/CRC, 2nd ed. United States of America on acid-free paper, 2005, ch. 1.
[19] T.S. Rappaport, “Wireless Communications Principles and Practice,” Prentice Hall PTR, 2nd ed. United States of America, 2002, ch. 4.
[20] S. Promwong, W. Hanitachi, J. Takada, P. Supanakoon and P. Tangtisanon, “Measurement and Analysis of UWB-IR Antenna Performance for WPANs,” Thammasat International Journal of Science and Technology (TIJSAT), pp. 56-62, Oct-Dec 2003.
[21] S. Promwong, W. Hanitachi, J. Takada, P. Supanakoon and P. Tangtisanon, “Measurement and Analysis of UWB-IR Antenna Performance for WPANs,” Thammasat International Journal of Science and Technology (TIJSAT), pp. 56-62, Oct-Dec 2003.