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A Maximum Likelihood TOA Based Estimator For Localization in Heterogeneous Networks

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DOI: 10.4236/ijcns.2010.31004    5,186 Downloads   10,436 Views   Citations

ABSTRACT

In this paper, we exploit the concept of data fusion in hybrid localization systems by combining different TOA (Time of Arrival) observables coming from different RATs (Radio Access Technology) and characterized by different precisions in order to enhance the positioning accuracy. A new Maximum Likelihood estimator is developed to fuse different measured ranges with different variances. In order to evaluate this estimator, Monte Carlo simulations are carried out in a generic environment and Cramer Rao Lower Bounds (CRLB) are investigated. This algorithm shows enhanced positioning accuracy at reasonable noise levels comparing to the typical Weighted Least Square estimator. The CRLB reveals that the choice of the number, and the configuration of Anchor nodes, and the type of RAT may enhance positioning accuracy.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

M. LAARAIEDH, S. AVRILLON and B. UGUEN, "A Maximum Likelihood TOA Based Estimator For Localization in Heterogeneous Networks," International Journal of Communications, Network and System Sciences, Vol. 3 No. 1, 2010, pp. 38-42. doi: 10.4236/ijcns.2010.31004.

References

[1] G. Shen, R. Zetik, and R. Thoma, “Performance comparison of TOA and TDOA based location estimation algorithms in los environment,” WPNC 08, 2008.
[2] Z. Sahinoglu, S. Gezici, and I. Guvenc, “Ultra-wideband positioning systems : Theoretical limits, ranging algo- rithms, and protocols,” Cambridge University Press, New York, 2008.
[3] B. Denis, J. Keignart, and N. Daniele, “Impact of nlos propagation upon ranging precision in UWB systems,” IEEE Conference on Ultra Wide Band and Systems and Technologies, 2003.
[4] M. Ciurana, F. Barcelo-Arroyo, and F. Izquierdo, “A ranging method with IEEE 802.11 data frames for indoor localization,” WCNC 2007, 2007.
[5] A. Gunther and C. Hoene, “Measuring round trip times to determine the distance between WLAN nodes,” Net- working, 2005.
[6] C. Mazzucco, U. Spagnolini, and G. Mulas, “A ranging technique for UWB indoor channel based on power delay profile analysis,” IEEE VTC Spring, 2004.
[7] M. Ciurana, F. Barcelo-Arroyo, and F. Izquierdo, “A ranging system with IEEE 802.11 data frames,” IEEE Radio and Wireless Symposium, January 2007.
[8] K. Cheung, W. K. Ma, and H. So, “Accurate appro- ximation algorithm for TOA-based maximum likelihood mobile location using semidefinite programming,” IEEE International Conference on Coustics, Speech, and Signal Processing, 2004.
[9] M. Laaraiedh, S. Avrillon, and B. Uguen, “Enhancing positioning accuracy through direct position estimators based on hybrid RSS data fusion,” IEEE VTC Spring, 2009.
[10] W. Kim, J. Lee, and G. Jee, “The interior-point method for an optimal treatment of bias in trilateration location,” IEEE Transactions on Vehicular Technology, Vol. 55, July 2006.
[11] M. Laaraiedh, S. Avrillon, and B. Uguen, “Hybrid data fusion techniques for localization in UWB networks,” WPNC 09, March 2009.

  
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