Vol. 25
Latest Volume
All Volumes
PIERB 105 [2024] PIERB 104 [2024] PIERB 103 [2023] PIERB 102 [2023] PIERB 101 [2023] PIERB 100 [2023] PIERB 99 [2023] PIERB 98 [2023] PIERB 97 [2022] PIERB 96 [2022] PIERB 95 [2022] PIERB 94 [2021] PIERB 93 [2021] PIERB 92 [2021] PIERB 91 [2021] PIERB 90 [2021] PIERB 89 [2020] PIERB 88 [2020] PIERB 87 [2020] PIERB 86 [2020] PIERB 85 [2019] PIERB 84 [2019] PIERB 83 [2019] PIERB 82 [2018] PIERB 81 [2018] PIERB 80 [2018] PIERB 79 [2017] PIERB 78 [2017] PIERB 77 [2017] PIERB 76 [2017] PIERB 75 [2017] PIERB 74 [2017] PIERB 73 [2017] PIERB 72 [2017] PIERB 71 [2016] PIERB 70 [2016] PIERB 69 [2016] PIERB 68 [2016] PIERB 67 [2016] PIERB 66 [2016] PIERB 65 [2016] PIERB 64 [2015] PIERB 63 [2015] PIERB 62 [2015] PIERB 61 [2014] PIERB 60 [2014] PIERB 59 [2014] PIERB 58 [2014] PIERB 57 [2014] PIERB 56 [2013] PIERB 55 [2013] PIERB 54 [2013] PIERB 53 [2013] PIERB 52 [2013] PIERB 51 [2013] PIERB 50 [2013] PIERB 49 [2013] PIERB 48 [2013] PIERB 47 [2013] PIERB 46 [2013] PIERB 45 [2012] PIERB 44 [2012] PIERB 43 [2012] PIERB 42 [2012] PIERB 41 [2012] PIERB 40 [2012] PIERB 39 [2012] PIERB 38 [2012] PIERB 37 [2012] PIERB 36 [2012] PIERB 35 [2011] PIERB 34 [2011] PIERB 33 [2011] PIERB 32 [2011] PIERB 31 [2011] PIERB 30 [2011] PIERB 29 [2011] PIERB 28 [2011] PIERB 27 [2011] PIERB 26 [2010] PIERB 25 [2010] PIERB 24 [2010] PIERB 23 [2010] PIERB 22 [2010] PIERB 21 [2010] PIERB 20 [2010] PIERB 19 [2010] PIERB 18 [2009] PIERB 17 [2009] PIERB 16 [2009] PIERB 15 [2009] PIERB 14 [2009] PIERB 13 [2009] PIERB 12 [2009] PIERB 11 [2009] PIERB 10 [2008] PIERB 9 [2008] PIERB 8 [2008] PIERB 7 [2008] PIERB 6 [2008] PIERB 5 [2008] PIERB 4 [2008] PIERB 3 [2008] PIERB 2 [2008] PIERB 1 [2008]
2010-09-14
Multi-Floor Indoor Positioning System Using Bayesian Graphical Models
By
Progress In Electromagnetics Research B, Vol. 25, 241-259, 2010
Abstract
In recent years, location determination systems have gained a high importance due to its rule in the context aware systems. In this paper, we will design a multi-floor indoor positioning system based on Bayesian Graphical Models (BGM). Graphical models have a great flexibility on visualizing the relationships between random variables. Rather of using one sampling technique, we are going to use multiple sets each set contains a collection of sampling techniques, the accuracy of each set will be compared with each other.
Citation
Abdullah Al-Ahmadi, Abdusamea. I. A. Omer, Muhammad Ramlee Kamarudin, and Tharek Bin Abdul Rahman, "Multi-Floor Indoor Positioning System Using Bayesian Graphical Models," Progress In Electromagnetics Research B, Vol. 25, 241-259, 2010.
doi:10.2528/PIERB10081202
References

1. Bahl, P. and V. Padmanabhan, "RADAR: An in-building RF-based user location and tracking system," IEEE INFOCOM, Vol. 2, 775-784, Citeseer, 2000.

2. Seidel, S. and T. Rappaport, "914MHz path loss prediction models for indoor wireless communications in multi oored buildings," IEEE Transactions on Antennas and Propagation, Vol. 40, No. 2, 207-217, 1992.
doi:10.1109/8.127405

3. Youssef, M. and A. Agrawala, "The Horus location determination system," Wireless Networks, Vol. 14, No. 3, 357-374, 2008.
doi:10.1007/s11276-006-0725-7

4. Tayebi, A., J. Gomez, F. Saez de Adana, and O. Gutierrez, "The application of ray-tracing to mobile localization using the direction of arrival and received signal strength in multipath indoor environments," Progress In Electromagnetics Research, Vol. 91, 1-15, 2009.
doi:10.2528/PIER09020301

5. Seow, C. and S. Tan, "Localization of omni-directional mobile device in multipath environments," Progress In Electromagnetics Research, Vol. 85, 323-348, 2008.
doi:10.2528/PIER08090302

6. Kanaan, M. and K. Pahlavan, "A comparison of wireless geolocation algorithms in the indoor environment," IEEE Wireless Communications and Networking Conference, 177-182, 2004.

7. Honkavirta, V., T. Perala, S. Ali-Loytty, and R. Piche, "A comparative survey of WLAN location fingerprinting methods," 6th Workshop on Positioning, Navigation and Communication WPNC, 2009.

8. Liu, H., H. Darabi, P. Banerjee, and J. Liu, "Survey of wireless indoor positioning techniques and systems," IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, Vol. 37, No. 6, 1067-1080, 2007.
doi:10.1109/TSMCC.2007.905750

9. Pandey, S. and P. Agrawal, "A survey on localization techniques for wireless networks," Journal --- Chinese Institute of Engineers, Vol. 29, No. 7, 1125, 2006.
doi:10.1080/02533839.2006.9671216

10. Wallbaum, M. and S. Diepolder, "Benchmarking wireless lan location systems," Proceedings of the 2005 Second IEEE International Workshop on Mobile Commerce and Services (WMCS 2005), 42-51, Munich, Germany, 2005.
doi:10.1109/WMCS.2005.7

11. Pahlavan, K. and P. Krishnamurthy, Principles of Wireless Networks, Prentice Hall PTR, New Jersey, 2002.

12. Kaemarungsi, K. and P. Krishnamurthy, "Properties of indoor received signal strength for WLAN location fingerprinting," Proceedings of the 1st Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MOBIQUITOUS04), 14-23, 2004.
doi:10.1109/MOBIQ.2004.1331706

13. Komar, C. and C. Ersoy, "Location tracking and location based service using IEEE 802.11 WLAN infrastructure," European Wireless, 24-27, 2004.

14. Tan, S., M. Tan, and H. Tan, "Multipath delay measurements and modeling for inter floor wireless communications," IEEE Transactions on Vehicular Technology, Vol. 49, No. 4, 1334-1341, Jul. 2000.
doi:10.1109/25.875253

15. Jensen, F., "Bayesian graphical models," Encyclopedia of Environmetrics, 2000.

16. Elnahrawy, E., R. Martin, W. Ju, P. Krishnan, and D. Madigan, "Bayesian indoor positioning systems," Infocom. Citeseer, 1217-1227, 2005.

17. Noble, W., "Getting started in probabilistic graphical models," PLoS Comput. Biol., Vol. 3, No. 12, 252, 2007.
doi:10.1371/journal.pcbi.0030252

18. Geman, S., D. Geman, K. Abend, T. Harley, and L. Kanal, "Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images*," Journal of Applied Statistics, Vol. 20, No. 5, 25-62, 1993.
doi:10.1080/02664769300000058

19. Cowles, M., Review of WinBUGS 1.4, Vol. 58, No. 4, 330-336, The American Statistician, 2004.

20. Ntzoufras, I., Bayesian Modeling Using WinBUGS, John Wiley & Sons Inc, 2009.
doi:10.1002/9780470434567

21. Hastings, W., "Monte Carlo sampling methods using Markov chains and their applications," Biometrika, Vol. 57, No. 1, 97-109, 1970.
doi:10.1093/biomet/57.1.97

22. Metropolis, N., A. Rosenbluth, M. Rosenbluth, A. Teller, E. Teller, et al. "Equation of state calculations by fast computing machines," The Journal of Chemical Physics, Vol. 21, No. 6, 1087, 1953.
doi:10.1063/1.1699114

23. Neal, R., "Slice sampling," Annals of Statistics, Vol. 31, No. 3, 705-741, 2003.
doi:10.1214/aos/1056562461

24. Neal, R. M., "Suppressing random walks in Markov chain Monte Carlo using ordered overrelaxation," Learning in Graphical Models, 205-225, 1998.

25. ``Netstumbler." [Online]. Available: http://www.netstumbler.com/.

26. ``inssider by metageek." [Online]. Available: http://www.metageek.net/.

27. ``Winbugs." [Online]. Available: http://www.mrcbsu.cam.ac.uk/bugs/.