Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-28T11:00:34.987Z Has data issue: false hasContentIssue false
  • English
  • Français

Indoor Global Localisation in Anchor-based Systems using Audio Signals

Published online by Cambridge University Press:  16 February 2016

João Moutinho ,
Diamantino Freitas  and
Rui Esteves Araújo
João Moutinho*
Affiliation:
(Institute for Systems and Computer Engineering, Technology and Science (INESC TEC)) (University of Porto – Faculty of Engineering)
Diamantino Freitas
Affiliation:
(University of Porto – Faculty of Engineering)
Rui Esteves Araújo
Affiliation:
(Institute for Systems and Computer Engineering, Technology and Science (INESC TEC)) (University of Porto – Faculty of Engineering)
*
(E-mail: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper presents a method that allows mobile devices to be globally self-localised in indoor localisation systems by transmitting to them data from position reference anchors. The objective is to establish a reliable one-way down-link communication through signals used in the localisation process in a typically strong fading and multipath channel environment. This is accomplished by using signal processing techniques, including coding and forward error correction, to transmit data using a specific transmission control protocol. Experimental results, using audio as the signal between anchors and the mobile device, demonstrate successful data transmission in realistic scenarios like a common noisy and reverberant room. Spread spectrum noise-like masked signals 4·9 dB below background noise were sufficient to attain correct data reception at four metres distance between a loudspeaker anchor and a mobile device's microphone.

Keywords

Indoor Global LocalisationSpread SpectrumEcho HidingGolay Codes
Type
Research Article
Information
The Journal of Navigation , Volume 69 , Issue 5 , September 2016 , pp. 1024 - 1040
Copyright
Copyright © The Royal Institute of Navigation 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Aguilera, T., Paredes, J., Alvarez, F., Suarez, J. and Hernandez, A. (2013). Acoustic Local Positioning System using an iOS Device. International Conference on Indoor Positioning and Indoor Navigation (IPIN), 1–8.Google Scholar
Amundson, I. and Koutsoukos, X. (2009). A Survey on Localization for Mobile Wireless Sensor Networks. Mobile Entity Localization and Tracking in GPS-less Environments, 5801, pp. 235–254.CrossRefGoogle Scholar
Boney, L., Tewfik, A. and Hamdy, K. (1996). Digital watermarks for audio signals. IEEE International Conference on Multimedia Computing and Systems, 473–480.CrossRefGoogle Scholar
Brignone, C., Connors, T., Lyon, G. and Pradhan, S. (2003). SmartLOCUS: An autonomous, self-assembling sensor network for indoor asset and systems management. Mobile Media Syst. Lab., HP Laboratories, Palo Alto, CA, Tech. Rep, 41.Google Scholar
Chen, J., Hudson, R. and Yao, Kung, (2002). Maximum-likelihood source localization and unknown sensor location estimation for wideband signals in the near-field. IEEE Transactions on Signal Processing, 50(8), 1843–1854.Google Scholar
Cheung, K. and So, H. (2005). A multidimensional scaling framework for mobile location using time-of-arrival measurements. IEEE Transactions on Signal Processing. 53(2), 460–470.Google Scholar
Cheung, K., So, H., Ma, W. and Chan, Y. (2006). A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality. EURASIP Journal of Advanced Signal Processing, 2006, 1–24.Google Scholar
Deak, G., Curran, K. and Condell, J. (2012). A survey of active and passive indoor localization systems. Computer Communications, 35(16), 1939–1954.Google Scholar
Fenwick, A. (1999). Algorithms for position fixing using pulse arrival times. IEE Proceedings - Radar , Sonar and Navigation, 146(4), 208–212.Google Scholar
Ferraro, R. and Aktihanoglu, M. (2011). Location-aware applications. Shelter Island, NY: Manning.Google Scholar
Garcia, R. (1999). Digital watermarking of audio signals using a psychoacoustic auditory model and spread spectrum theory. Audio Engineering Society Convention 107, Audio Engineering Society.Google Scholar
Golay, M. (1949). Notes on Digital Coding. Proceedings of the Institute of Radio Engineers (IRE), 37(6), 657.Google Scholar
Gruhl, D., Bender, W. and Lu, A. (1996). Echo hiding in Information Hiding. 1st International Workshop, 1174 (Berlin, Germany: Springer-Verlag), 295–315.Google Scholar
Gu, Y., Song, Q., Li, Y. and Ma, M. (2014). Foot-mounted Pedestrian Navigation based on Particle Filter with an Adaptive Weight Updating Strategy. Journal of Navigation, 68(1), 23–38.Google Scholar
Guven, U. (2014). Performance Analysis of Efficient Channel Coding Schemes for Deep Space and Interplanetary Missions. Research & Reviews: Journal of Space Science & Technology, 3(2), 15–21.Google Scholar
Houghton, A. (2012). Error coding for engineers (Vol. 641). Springer Science & Business Media.Google Scholar
Hatfull, F. (2011). Watermarking Audio Data – A survey and Comparison of Techniques for Audio Steganography. Case Western Reserve University.Google Scholar
Jeub, M., Schäfer, M. and Vary, P. (2009). A binaural room impulse response database for the evaluation of dereverberation algorithms. 16th International Conference on IEEE Digital Signal Processing, 1–5.Google Scholar
Johnston, J. (1988). Transform coding of audio signals using perceptual noise criteria. IEEE Journal on Selected Areas in Communications, 6(2), 314–323.Google Scholar
Kaplan, E. and Hegarty, C. (Eds.). (2005). Understanding GPS: principles and applications. Artech house.Google Scholar
Lopes, S., Vieira, J., Reis, J., Albuquerque, D. and Carvalho, N. (2014). Accurate smartphone indoor positioning using a WSN infrastructure and non-invasive audio for TDoA estimation. Pervasive and Mobile Computing, 20, 29–46.Google Scholar
Merry, L. A., Faragher, R. M., and Scheding, S. (2010). Comparison of opportunistic signals for localisation. In Proceedings of the 7th IFAC Symposium on Intelligent Autonomous Vehicles, Lecce, Italy, 6–8.Google Scholar
Moutinho, J., Araújo, R. and Freitas, D. (2013). Sound based Indoor Localization – Practical Implementation Considerations. Indoor Positioning and Indoor Navigation (IPIN) International Conference on, IEEE, 109–112.Google Scholar
Muñoz, D., Bouchereau, F., Vargas, and Caldera, R. (2009). Position location techniques and applications. Academic Press.Google Scholar
Prieto, J., Jiménez, A. and Guevara, J. (2007). Subcentimeter-accuracy localization through broadband acoustic transducers. IEEE International Symposium on Intelligent Signal Processing. 1–6.Google Scholar
Proakis, J. (2003). Spread spectrum signals for digital communications. John Wiley & Sons, Inc.Google Scholar
Singh, B., Kumar Sahoo, S. and Ranjan Pradhan, S. (2012). Performance Evaluation of Anchor-based Range-based Localization Systems in Wireless Sensor Networks. International Journal of Computer Applications, 52(17), 24–29.Google Scholar
Suzuki, A., Iyota, T., Choi, Y., Kubota, Y. and Watanabe, K. (2009). Measurement accuracy on indoor positioning system using spread spectrum ultrasonic waves. 4th International Conference on Autonomous Robots and Agents - ICARA 2009, 294–297.Google Scholar
Truong, T., Holmes, J., Reed, I. and Yin, X. (1988). A simplified procedure for decoding the (23, 12) and (24, 12) Golay codes. TDA Progress Report, 42(96), 49–58.Google Scholar
Wei, H., Wan, Q., Chen, Z. and Ye, S. (2008). Multidimensional scaling-based passive emitter localization from range-difference measurements. IET Signal Processing, 2(4), 415–423.Google Scholar
Zekavat, S. and Buehrer, R. (2011). Handbook of position location: Theory, practice and advances (Vol. 27). John Wiley & Sons.Google Scholar