On the Analysis of Localization Accuracy of Wireless Indoor Positioning Systems using Cramer's Rule
This paper presents an analysis of the localization accuracy of indoor positioning systems using Cramer-s rule via IEEE 802.15.4 wireless sensor networks. The objective is to study the impact of the methods used to convert the received signal strength into the distance that is used to compute the object location in the wireless indoor positioning system. Various methods were tested and the localization accuracy was analyzed. The experimental results show that the method based on the empirical data measured in the non line-of-sight (NLOS) environment yield the highest localization accuracy; with the minimum error distance less than 3 m.
[1] G.M. Djuknic, R.E. Richton, "Geolocation and assisted GPS," IEEE
Computer, vol. 34, February 2001, pp. 123 - 125.
[2] M.U. Rehman, Y. Gao, X. Chen, C.G. Parini, Z. Ying,
"Characterisation of System Performance of GPS Antennas in Mobile
Terminals Including Environmental Effects," European Conference on
Antennas and Propagation, March 2009, pp. 1832 - 1836.
[3] N. Sghaier, A. Mellouk, B. Augustin, Y. Amirat, J. Marty, M.E.A.
Khoussa, A. Abid, R. Zitouni, "Wireless Sensor Networks for medical
care services," Wireless Communications and Mobile Computing
Conference, July 2011, pp. 571 - 576.
[4] J. Salter, B. Li, D. Woo, A.G. Dempster, C. Rizos, "802.11 Positioning
in the Home," Consumer Communications and Networking Conference,
January 2008, pp. 598 - 602.
[5] H.K. Parikh, W.R. Michalson, "Error mechanisms in an RF-based
indoor positioning system," International Conference on Acoustics
Speech and Signal Processing, March - April 2008, pp. 5320 - 5323
[6] W.H. Kuo, Y.S. Chen, G.T. Jen, T.W. Lu, "An intelligent positioning
approach: RSSI-based indoor and outdoor localization scheme in
ZigBee networks," Machine Learning and Cybernetics, vol. 6, July
2010, pp. 2754 - 2759.
[7] J. Larranaga, L. Muguira, J.M. Lopez-Garde, J.I. Vazquez, "An
environment adaptive ZigBee-based indoor positioning algorithm,"
Indoor Positioning and Indoor Navigation, September 2010, pp. 1 - 8.
[8] Y. Lim, J. Park, "Practical indoor positioning system using received
signal strength in IEEE 802.15.4 networks," International Conference
on Consumer Electronics, January 2009, pp. 1 - 2.
[9] K. Yu, Y.J. Guo, "Improving anchor position accuracy for 3-D
localization in wireless sensor networks," IEEE International
Conference on Communication, May 2008, pp. 951 - 955.
[10] J. Liang, J. Shao, Y. Xu, J. Tan, B.T. Davis, P.L. Bergstrom, "Sensor
Network Localization in Constrained 3-D Spaces," IEEE International
Conference on Mechatronics and Automation, June 2006, pp. 49 - 54.
[11] B. Cooperstein, "Elementary Linear Algebra," University of California,
Santa Cruz, January 2006, pp. 312-323.
[12] A. Bose, C.H. Foh, "A practical path loss model for indoor WiFi
positioning enhancement," International Conference on Information
Communications and Signal Processing, December 2009, pp. 1-5.
[1] G.M. Djuknic, R.E. Richton, "Geolocation and assisted GPS," IEEE
Computer, vol. 34, February 2001, pp. 123 - 125.
[2] M.U. Rehman, Y. Gao, X. Chen, C.G. Parini, Z. Ying,
"Characterisation of System Performance of GPS Antennas in Mobile
Terminals Including Environmental Effects," European Conference on
Antennas and Propagation, March 2009, pp. 1832 - 1836.
[3] N. Sghaier, A. Mellouk, B. Augustin, Y. Amirat, J. Marty, M.E.A.
Khoussa, A. Abid, R. Zitouni, "Wireless Sensor Networks for medical
care services," Wireless Communications and Mobile Computing
Conference, July 2011, pp. 571 - 576.
[4] J. Salter, B. Li, D. Woo, A.G. Dempster, C. Rizos, "802.11 Positioning
in the Home," Consumer Communications and Networking Conference,
January 2008, pp. 598 - 602.
[5] H.K. Parikh, W.R. Michalson, "Error mechanisms in an RF-based
indoor positioning system," International Conference on Acoustics
Speech and Signal Processing, March - April 2008, pp. 5320 - 5323
[6] W.H. Kuo, Y.S. Chen, G.T. Jen, T.W. Lu, "An intelligent positioning
approach: RSSI-based indoor and outdoor localization scheme in
ZigBee networks," Machine Learning and Cybernetics, vol. 6, July
2010, pp. 2754 - 2759.
[7] J. Larranaga, L. Muguira, J.M. Lopez-Garde, J.I. Vazquez, "An
environment adaptive ZigBee-based indoor positioning algorithm,"
Indoor Positioning and Indoor Navigation, September 2010, pp. 1 - 8.
[8] Y. Lim, J. Park, "Practical indoor positioning system using received
signal strength in IEEE 802.15.4 networks," International Conference
on Consumer Electronics, January 2009, pp. 1 - 2.
[9] K. Yu, Y.J. Guo, "Improving anchor position accuracy for 3-D
localization in wireless sensor networks," IEEE International
Conference on Communication, May 2008, pp. 951 - 955.
[10] J. Liang, J. Shao, Y. Xu, J. Tan, B.T. Davis, P.L. Bergstrom, "Sensor
Network Localization in Constrained 3-D Spaces," IEEE International
Conference on Mechatronics and Automation, June 2006, pp. 49 - 54.
[11] B. Cooperstein, "Elementary Linear Algebra," University of California,
Santa Cruz, January 2006, pp. 312-323.
[12] A. Bose, C.H. Foh, "A practical path loss model for indoor WiFi
positioning enhancement," International Conference on Information
Communications and Signal Processing, December 2009, pp. 1-5.
@article{"International Journal of Electrical, Electronic and Communication Sciences:58573", author = "Kriangkrai Maneerat and Chutima Prommak", title = "On the Analysis of Localization Accuracy of Wireless Indoor Positioning Systems using Cramer's Rule", abstract = "This paper presents an analysis of the localization accuracy of indoor positioning systems using Cramer-s rule via IEEE 802.15.4 wireless sensor networks. The objective is to study the impact of the methods used to convert the received signal strength into the distance that is used to compute the object location in the wireless indoor positioning system. Various methods were tested and the localization accuracy was analyzed. The experimental results show that the method based on the empirical data measured in the non line-of-sight (NLOS) environment yield the highest localization accuracy; with the minimum error distance less than 3 m.
", keywords = "Indoor positioning systems, localization accuracy, wireless networks, Cramer's rule.", volume = "5", number = "12", pages = "1790-5", }
