Skip to main content
  • Research Article
  • Open access
  • Published:

Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization

Abstract

Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS) errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.). In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS), even when nearly half the measures suffered from NLOS or other coarse errors.

References

  1. European Commission : Directive 2002/58/EC on Privacy and Electronic Communications. 2002.

    Google Scholar 

  2. Docket CC: Revision of the commission rule to ensure compatibility with enhanced 911 emergency calling system. Federal Communications Commission Reports and Orders 96–264 1996.

    Google Scholar 

  3. Pahlavan K, Li X, Makela JP: Indoor geolocation science and technology. IEEE Communications Magazine 2002, 40(2):112–118. 10.1109/35.983917

    Article  Google Scholar 

  4. Borestein J, Everett HR, Feng L: Where Am I? Sensors and Methods for Mobile Robot Positioning. University of Michigan, Ann Arbor, Mich, USA; 1996.

    Google Scholar 

  5. Bahl P, Padmanabhan VN: RADAR: an in-building RF-based user location and tracking system. Proceedings of 19th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '00), March 2000, Tel Aviv, Israel 2: 775–784.

    Google Scholar 

  6. Anastasi G, Bandelloni R, Conti M, Delmastro F, Gregori E, Mainetto G: Experimenting an indoor bluetooth-based positioning service. Proceedings of 23rd International Conference on Distributed Computing Systems Workshops (ICDCS '03), May 2003, Providence, RI, USA 480–483.

    Google Scholar 

  7. Ekahau Positioning Engine https://doi.org/www.ekahau.com

  8. Povescu I, Nafomita I, Constantinou P, Kanatas A, Moraitis N: Neural networks applications for the prediction of propagation pathloss in urban environments. Proceedings of 53rd IEEE Semi-Annual Vehicular Technology Conference (VTC '01), May 2001, Rhodes, Greece 1: 387–391.

    Article  Google Scholar 

  9. Kim W, Jee G-I, Lee J: Wireless location with NLOS error mitigation in Korean CDMA system. Proceedings of the 2nd International Conference on 3G Mobile Communication Technologies, March 2001, London, UK 134–138.

    Google Scholar 

  10. Venkatraman S, Caffery J Jr.: Statistical approach to non-line-of-sight BS identification. Proceedings of the 5th International Symposium on Wireless Personal Multimedia Communications, October 2002, Honolulu, Hawaii, USA 1: 296–300.

    Article  Google Scholar 

  11. Venkatraman S, Caffery Jr J, You H-R: Location using LOS range estimation in NLOS environments. Proceedings of IEEE 55th Vehicular Technology Conference (VTC '02), 2002, Birmingham, Ala, USA 2: 856–860.

    Google Scholar 

  12. Chen P-C: A non-line-of-sight error mitigation algorithm in location estimation. Proceedings of IEEE Wireless Communications and Networking Conference (WCNC '99), September 1999, New Orleans, La, USA 1: 316–320.

    Google Scholar 

  13. Casas R, Gracia HJ, Marco A, Falcó JL: Synchronization in wireless sensor networks using Bluetooth. Proceedings of the 3rd International Workshop on Intelligent Solutions in Embedded Systems (WISES '05), May 2005, Hamburg, Germany 79–88.

    Google Scholar 

  14. Foy WH: Position-location solutions by taylor-series estimation. IEEE Transactions on Aerospace and Electronic Systems 1976, 12: 187–193.

    Article  Google Scholar 

  15. Ghidary SS, Tani T, Takamori T, Hattori M: A new home robot positioning system (HRPS) using IR switched multi ultrasonic sensors. Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (SMC '99), October 1999, Tokyo, Japan 4: 737–741.

    Google Scholar 

  16. Mahajan A, Walworth M: 3D position sensing using the differences in the time-of-flights from a wave source to various receivers. IEEE Transactions on Robotics and Automation 2001, 17(1):91–94. 10.1109/70.917087

    Article  Google Scholar 

  17. Manolakis DE: Efficient solution and performance analysis of 3-D position estimation by trilateration. IEEE Transactions on Aerospace and Electronic Systems 1996, 32(4):1239–1248. 10.1109/7.543845

    Article  Google Scholar 

  18. Manolakis DE, Cox ME: Effect in range difference position estimation due to stations' position errors. IEEE Transactions on Aerospace and Electronic Systems 1998, 34(1):329–334. 10.1109/7.640291

    Article  Google Scholar 

  19. Girod L, Estrin D: Robust range estimation using acoustic and multimodal sensin. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '01), October–November 2001, Maui, Hawaii, USA 3: 1312–1320.

    Google Scholar 

  20. Bohn D: Environmental effects on the speed of sound. Journal of the Audio Engineering Society 1988, 36(4):223–231.

    MathSciNet  Google Scholar 

  21. Zhang Z: Parameter estimation techniques: a tutorial with application to conic fitting. In Rapport de recherche RR-2676. INRIA, Sophia-Antipolis, France; 1995.

    Google Scholar 

  22. Mintz D, Meer P, Rosenfeld A: Analysis of the least median of squares estimator for computer vision applications. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '92), June 1992, Champaign, Ill, USA 621–623.

    Google Scholar 

  23. Rousseeuw PJ, Leroy AM: Robust Regression and Outlier Detection. John Wiley & Sons, New Yourk, NY, USA; 1987.

    Book  Google Scholar 

  24. Fischler MA, Bolles RC: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Communications of the ACM 1981, 24(6):381–395. 10.1145/358669.358692

    Article  MathSciNet  Google Scholar 

  25. Ray PK, Mahajan A: Optimal configuration of receivers in an ultrasonic 3D position estimation system by using genetic algorithms. Proceedings of the American Control Conference, June 2000, Chicago, Ill, USA 4: 2902–2906.

    Google Scholar 

  26. Moses RL, Krishnamurthy D, Patterson RM: A self-localization method for wireless sensor networks. EURASIP Journal on Applied Signal Processing 2003, 4: 348–358.

    MATH  Google Scholar 

  27. Addlesee M, Curwen R, Hodges S, et al.: Implementing a sentient computing system. IEEE Computer 2001, 34(8):50–56. 10.1109/2.940013

    Article  Google Scholar 

  28. Priyantha NB, Chakraborty A, Balakrishnan H: The Cricket location-support system. Proceedings of the 6th Annual International Conference on Mobile Computing and Networking (MobiCom '00), August 2000, Boston, Mass, USA 32–43.

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R. Casas.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Casas, R., Marco, A., Guerrero, J.J. et al. Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization. EURASIP J. Adv. Signal Process. 2006, 043429 (2006). https://doi.org/10.1155/ASP/2006/43429

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1155/ASP/2006/43429

Keywords