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Wireless Indoor Positioning Method with Evaluation of Channel Propagation Model by TR-FMM

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Abstract

The positioning method based on time of flight (TOF) measurement, link the time delay to the position of the small mobile communications terminal to be located. Its accuracy depends on the suitability of the channel propagating model used for the actual wireless positioning system. In an indoor wireless network, the propagating condition is very difficult to predict due to indoor environment is variable, which comes from variant room layout or staff activities. In this paper, we present a novel method which dynamically estimates the propagating model based on an inverse evaluation procedure, using only received measurement TOF obtained by the fixed access points (APs) in real time. This method is a combination of simultaneous algebraic reconstruction technique and fast matching method (FMM). Once the optimized propagating model is estimated, it is possible to accurately determine the position of MS using our existing time reversal (TR) method, a positioning method employ transceivers interoperability principles for the MS and each AP. The proposed TR-FMM method is validated by simulations. These results show that it has great advantages in accuracy and complexity for indoor positioning system. The positioning deviation is about 3.2 cm based on the simulative analysis, and the accuracy of the positioning is improved 23.66 times with taking about 2 min comparing to the time reversal without the channel information.

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References

  1. Panzieri, S., Pascucci, F., & Ulivi, G. (2002). An outdoor navigation system using GPS and inertial platform. IEEE/ASME Transactions on Mechatronics, 7(2), 134–142.

    Article  Google Scholar 

  2. Girod, L., & Estrin, D. (2001). Robust range estimation using acoustic and multimodal sensing. In IEEE/RSJ international conference on intelligent robots and systems (IROS’01). Hawaii, USA (pp. 1312–1320).

  3. Guoping, Z., Krishnan, S., & Chin, F. et al. (2008). UWB multicell indoor localization experiment system with adaptive TDOA combination. In 2008 IEEE 68th vehicular technology conference (Vol. 2, pp. 604–608).

  4. Niculescu, D., & Nath, B. (2003). AdHoc positioning system (APS) using AOA. In 22nd annual joint conference of the IEEE computer and communications societies (INFOCOM’2003). IEEE (pp. 1734–1174).

  5. Xu, K., Chen, M., & Liu, Y. (2008). A novel localization algorithm based on received signal strength indicator. In Computer science and information technology, 2008. ICCSIT’ (pp. 249–253).

  6. Chen, X. (2012). Industrial control and electronics engineering (ICICEE). In 2012 international conference on date of conference (pp. 871–873).

  7. Hossain, S. (2012). Accuracy enhancement of fingerprint indoor positioning system. In Intelligent systems, modelling and simulation (ISMS), 2012 third international conference on (pp. 600–605).

  8. Xia, Y., & Fu, Y. (2012). Refocusing with time reversal mirror in random medium. Procedia Engineering, 29, 2600–2604.

    Article  Google Scholar 

  9. Hristova, Y., Kuchment, P., & Nguyen, L. (2008). Reconstruction and time reversal in thermoacoustic tomography in acoustically homogeneous and inhomogeneous media. Inverse Problems, 24(5), 055006.

    Article  MathSciNet  Google Scholar 

  10. Hristova, Y. (2009). Time reversal in thermoacoustic tomography—an error estimate. Inverse Problems, 25(5), 055008.

    Article  MathSciNet  Google Scholar 

  11. Agranovsky, M., & Kuchment, P. (2007). Uniqueness of reconstruction and an inversion procedure for thermoacoustic and photoacoustic tomography. Inverse Problems, 23(5), 2089–2102.

    Article  MATH  MathSciNet  Google Scholar 

  12. Joo, J.-H., & Kim, J.-S. (2010). Nulling crosstalk in underwater communication with an adaptive time-reversal mirror. In Proceedings of symposium on ultrasonic electronics (Vol. 31, pp. 443–444).

  13. Marsac, L., Pernot, M., & Aubry, J.-F. (2010). Transcranial ultrasonic therapy based on time reversal of acoustically induced cavitation. IEEE Transactions on Biomedical Engineering, 57(1), 134–144.

    Article  Google Scholar 

  14. Borcea, L., Papanicolaou, G., Tsogka, C., et al. (2002). Imaging and time reversal in random media. Inverse Problems, 18(5), 1247–1279.

    Article  MATH  MathSciNet  Google Scholar 

  15. Zhang, W. (2010). Through-the-wall target localization with time reversal music method. Progress in Electromagnetics Research, 106, 75–89.

    Article  Google Scholar 

  16. Pan, X., Li, J., Xu, W., et al. (2010). Robust time reversal processing for active detection of a small bottom target in a shallow water waveguide. Journal of Zhejiang University Science C, 11(5), 401–406.

    Article  Google Scholar 

  17. Pradaa, C., & Thomas, J.-L. (2003). Experimental subwavelength localization of scatterers by decomposition of the time reversal operator interpreted as a covariance matrix. Journal Acoustical Society of America, 114(1), 235–243.

    Article  Google Scholar 

  18. Yun, Z., & Iskander, M. F. (2006). Time reversal with single antenna systems in indoor multipath environments: Spatial focusing and time compression. In Antennas and propagation society international symposium 2006, IEEE. IEEE (pp. 695–698).

  19. Sethian, J. A. (1996). A fast level set method for monotonically advancing fronts. Proceedings of the National Academy of Sciences, 93, 591–1595.

    Article  Google Scholar 

  20. Sethian, J. A. (2001). Evolution, implementation, and application of level set and fast marching methods for advancing fronts. Journal of Computational Physics, 169(2), 503–555.

    Article  MATH  MathSciNet  Google Scholar 

  21. Gu, Y., Lo, A., & Niemegeers, I. (2009). A survey of indoor positioning systems for wireless personal networks. Communications Surveys & Tutorials, IEEE, 11(1), 13–32.

    Article  Google Scholar 

  22. Andersen, A., & Kak, A. (1984). Simultaneous algebraic reconstruction technique (SART). Ultrasonic Imaging, 6, 81–94.

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the Chongqing Education Commission program KJ100520, Natural Science Foundation Project of CQ CSTC No. 2010BB2419, CQUPT scientific research foundation A2009-23.

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Authors and Affiliations

  1. College of Electronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Guoping Chen

  2. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Li Wang & Baike Zhang

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  1. Guoping Chen
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  2. Li Wang
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  3. Baike Zhang
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Correspondence to Baike Zhang.

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Chen, G., Wang, L. & Zhang, B. Wireless Indoor Positioning Method with Evaluation of Channel Propagation Model by TR-FMM. Wireless Pers Commun 81, 1199–1214 (2015). https://doi.org/10.1007/s11277-014-2179-z

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  • DOI: https://doi.org/10.1007/s11277-014-2179-z

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