Journal of Advanced Marine Engineering and Technology

The Korean Society of Marine Engineering (한국마린엔지니어링학회)
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Robust Relative Localization Using a Novel Modified Rounding Estimation Technique

  • Cho, Hyun-Jong (Advanced Development Team, Sangsin Brake) ;
  • Kim, Won-Yeol (Department of Electrical and Electronics Engineering, Korea Maritime and Ocean University) ;
  • Joo, Yang-Ick (Department of Electrical and Electronics Engineering, Korea Maritime and Ocean University) ;
  • Seo, Dong-Hoan (Division of Electrical and Electronics Engineering, Korea Maritime and Ocean University)
  • Received : 2014.12.03
  • Accepted : 2015.01.19
  • Published : 2015.02.28
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Abstract

Accurate relative location estimation is a key requirement in indoor localization systems based on wireless sensor networks (WSNs). However, although these systems have applied not only various optimization algorithms but also fusion with sensors to achieve high accuracy in position determination, they are difficult to provide accurate relative azimuth and locations to users because of cumulative errors in inertial sensors with time and the influence of external magnetic fields. This paper based on ultra-wideband positioning system, which is relatively suitable for indoor localization compared to other wireless communications, presents an indoor localization system for estimating relative azimuth and location of location-unaware nodes, referred to as target nodes without applying any algorithms with complex variable and constraints to achieve high accuracy. In the proposed method, the target nodes comprising three mobile nodes estimate the relative distance and azimuth from two reference nodes that can be installed by users. In addition, in the process of estimating the relative localization information acquired from the reference nodes, positioning errors are minimized through a novel modified rounding estimation technique in which Kalman filter is applied without any time consumption algorithms. Experimental results show the feasibility and validity of the proposed system.

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References

  1. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: A survey", Computer Networks, vol. 38, no. 4, pp. 393-422, 2002. https://doi.org/10.1016/S1389-1286(01)00302-4
  2. L. Zhang, Q. Cheng, Y. Wang, and S. Zeadally, "A novel distributed sensor positioning system using the dual of target tracking", IEEE Transaction on Computers, vol. 57, no. 2, pp. 246-260, 2008. https://doi.org/10.1109/TC.2007.70792
  3. H. Alemdar and C. Ersoy, "Wireless sensor networks for healthcare : A survey", Computer Networks, vol. 54, no. 15, pp. 2688-2710, 2010. https://doi.org/10.1016/j.comnet.2010.05.003
  4. E. L. van den Broek, "Ubiquitous emotion-aware computing", Personal and Ubiquitous Computing, vol. 17, no. 1, pp. 53-67, 2013. https://doi.org/10.1007/s00779-011-0479-9
  5. http://www.webpronews.com/ces-2012-google-mapsindoors-of-las-vegas-hotels-2012-01, Accessed August 20, 2012.
  6. P. Mirowski, P. Whiting, H. Steck, R. Palaniappan, M. MacDonald, D. Hartmann, and T. K. Ho, "Probability kernel regression for WiFi localisation", Journal of Location Based Services, vol. 6, no. 2, pp. 81-100, 2012. https://doi.org/10.1080/17489725.2012.694723
  7. L. Chen, B. Li, K. Zhao, C. Rizos, and Z. Zheng, "An Improved Algorithm to Generate a Wi-Fi Fingerprint Database for Indoor Positioning", Sensors, vol. 13, no. 8, pp. 11085-11096, 2013. https://doi.org/10.3390/s130811085
  8. http://www.ZigBee.org/en/about/faq.asp, Accessed December 10, 2011.
  9. C. H. Oh, "Location estimation using space time signal processing in RFID wireless sensor networks", International Journal of Distributed Sensor Networks, vol. 2013, Article ID 634531, p. 8, 2013.
  10. J. Wang, Q. Gao, Y. Yu, H. Wang, and M. Jin, "Toward robust indoor localization based on bayesian filter using chirp-spread-spectrum ranging", IEEE Transactions on Industrial Electronics, vol. 59, no. 3, pp. 1622-1629, 2012. https://doi.org/10.1109/TIE.2011.2165462
  11. X. Shen, M. Guizani, R. C. Qiu, and T. Le-Ngoc, Ultra-Wideband Wireless Communications and Networks, John Wiley, 2006.
  12. M. Mahfouz, C. Zhang, B. Merkl, M. Kuhn, and A. E. Fathy. "Investigation of high-accuracy indoor 3-D positioning using UWB technology", IEEE transaction on Microwave Theory and Technology, vol. 56, no. 6, pp. 1316-1330, 2008. https://doi.org/10.1109/TMTT.2008.923351
  13. Z. Zhang, H. Li, D. Yang, and C.Pei, "Collaborative compressed spectrum sensing : What if spectrum is not sparse?", IEEE Electronics Letters, vol. 47, no. 8, pp. 519-520, 2011. https://doi.org/10.1049/el.2011.0274
  14. D. Yang, H. Li, Z. Zhang, and G.D. Peterson, "Compressive sensing based sub-mm accuracy UWB positioning systems : A spaceCtime approach", Digital Signal Processing, vol. 23, no. 1, pp. 340-354, 2012. https://doi.org/10.1016/j.dsp.2012.07.012
  15. G. Garcia, L. Muppirisetty, and H. Wymeersch, "On the trade-off between accuracy and delay in UWB navigation", IEEE Communications Letters, vol. 17, no. 1, pp. 39-42, 2013. https://doi.org/10.1109/LCOMM.2012.120312.121542
  16. H. Jiang, C. Liu, Y. Zhang, and H. Cui, "Fast 3D node localization in multipath for UWB wireless sensor networks using modified propagator method", International Journal of Distributed Sensor Networks, vol. 2014, Article ID 312535, p. 8, 2014.
  17. X. Liu, G. Zhao, and X. Ma, "Target localization and tracking in noisy binary sensor networks with known spatial topology", Wireless Communications and Mobile Computing, vol. 9, no. 8, pp. 1028-1039, 2009. https://doi.org/10.1002/wcm.652
  18. M. P.Michaelides and C. G. Panayiotou, "SNAP : fault tolerant event location estimation in sensor networks using binary data", IEEE Transactions on Computers, vol. 58, no. 9, pp. 1185-1197, 2009. https://doi.org/10.1109/TC.2009.60
  19. E. Masazade, R. Niu, P. K. Varshney, and M. Keskinoz, "Energy aware iterative source localization for wireless sensor networks", IEEE Transactions on Signal Processing, vol. 58, no. 9, pp. 4824-4835, 2010. https://doi.org/10.1109/TSP.2010.2051433
  20. W. Meng, W. Xiao, and L. Xie, "An efficient EM algorithm for energy-based multisource localization in wireless sensor networks", IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 3, pp. 1017-1027, 2011. https://doi.org/10.1109/TIM.2010.2047035
  21. L. Cheng, C. D. Wu, Y. Z. Zhang, and Y. Wang, "Indoor robot localization based on wireless sensor networks", IEEE Transactions on Consumer Electronics, vol. 57, no. 3, pp. 1099-1104, 2011. https://doi.org/10.1109/TCE.2011.6018861
  22. S. W. Lee, D. Y. Lee, and C. W. Lee, "Enhanced DV-Hop algorithm with reduced hop-size error in ad hoc networks", IEICE Transactions on Communications, vol. 94, no. 7, pp. 2130-2132, 2011.
  23. J. Lee, W. Chung, and E. Kim, "A new range-free localization method using quadratic programming", Computer Communications, vol. 34, no. 8, pp. 998-1010, 2011. https://doi.org/10.1016/j.comcom.2010.10.013
  24. Z. Zhong and T. He, "RSD : A metric for achieving rangefree localization beyond connectivity", IEEE Transactions on Parallel and Distributed Systems, vol. 22, no. 11, pp. 1943-1951, 2011. https://doi.org/10.1109/TPDS.2011.105
  25. K. Lu, X. Xiang, D. Zhang, R. Mao, and Y. Feng, "Localization algorithm based on maximum a posteriori in wireless sensor networks", International Journal of Distributed Sensor Networks, vol. 2012, Article ID 260302, p. 7, 2012.
  26. L. Cheng, C. Wu, Y. Zhang, H. Wu, M. Li, and C. Maple, "A survey of localization in wireless sensor network", International Journal of Distributed Sensor Networks, vol. 2012, Article ID 962523, p. 12, 2012.
  27. P. Biswas, T.C. Liang, K. C. Toh, Y. Ye, and T. C. Wang, "Semidefinite Programming Approaches for Sensor Network Localization with Noisy Distance Measurements", IEEE Transactions on Automation Science and Engineering, vol. 3, no. 4, pp. 360-371, 2006. https://doi.org/10.1109/TASE.2006.877401
  28. P. Tseng, "Second-order cone programming relaxation of sensor network localization", SIAM Journal on Optimization, vol. 18, no. 1, pp. 156-185, 2007. https://doi.org/10.1137/050640308
  29. K. Yang, G. Wang, and Z.-Q. Luo, "Efficient convex relaxation methods for robust target localization by a sensor network using time differences of arrivals", IEEE Transactions on Signal Processing, vol. 57, no. 7, pp. 2775-2784, 2009. https://doi.org/10.1109/TSP.2009.2016891
  30. Y. Noam and H. Messer, "Notes on the tightness of the hybrid cramer-rao lower bound", IEEE Transaction on Signal Processing, vol. 57, no. 6, pp. 2074-2084, 2009. https://doi.org/10.1109/TSP.2009.2015113
  31. W. Y. Chiu, B. S. Chen, and C. Y. Yang, "Robust relative location estimation in wireless sensor networks with inexact position problems", IEEE Transactions on Mobile Computing, vol. 11, no. 6, pp. 935-946, 2012. https://doi.org/10.1109/TMC.2011.111
  32. Y. Chon and H. Cha, "LifeMap : A smartphone-based context provider for location-based services", IEEE Pervasive Computing, vol. 10, no. 2, pp. 58-67, 2011. https://doi.org/10.1109/MPRV.2011.13
  33. B. G. Lee and W. Y. Chung, "Multitarget threedimensional indoor navigation on a PDA in a wireless sensor network", IEEE Sensors Journal, vol. 11, no. 3, pp. 799-807, 2011. https://doi.org/10.1109/JSEN.2010.2076802
  34. A. R. J. Ruiz, F. S. Granja, J. C. Prieto Honorate, and J. I. G. Rosas, "Accurate pedestrian indoor navigation by tightly coupling foot-mounted IMU and RFID measurements", IEEE Transaction on Instrument and Measurement, vol. 61, no. 1, pp. 178-189. 2012. https://doi.org/10.1109/TIM.2011.2159317
  35. R. Zhang, F. Hoflinger, and L. Reindl, "Inertial sensor based indoor localization and monitoring system for emergency responders", IEEE Sensors Journal, vol. 13, no. 2, pp. 838-848, 2013. https://doi.org/10.1109/JSEN.2012.2227593
  36. H. J. Cho, Y. S. Ha, J. H. Kim, K. S. Ryu, and D. H. Seo, "Convergence localization system for self-localization based on estimation of relative coordinates", International Symposium on Marine Engineering & Technology, pp.80-83, 2013.
  37. H. J. Cho, J. S. Kim, S. G. Lee, J. W. Kim, and D. H. Seo, "Fixed node reduction technique using relative coordinate estimation algorithm", Journal of the Korean Society of Marine Engineering, vol. 37, no. 2, pp. 220-226, 2013. https://doi.org/10.5916/jkosme.2013.37.2.220

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