Terrain/clutter based location prediction by using multi-condition Bayesian decision theory

Authors:
A. Muhammad;M. S. Mazliham;Patrice Boursier;M. Shahrulniza;Jawahir Che Mustapha Yusuf
Affiliations:
Universiti Kuala Lumpur (UniKL MIIT), Kuala Lumpur Malaysia and Université de La Rochelle, France;Universiti Kuala Lumpur (UniKL MFI), Bandar Baru Bangi, Malaysia;Université de La Rochelle, France;Universiti Kuala Lumpur (UniKL MIIT), Kuala Lumpur, Malaysia;Universiti Kuala Lumpur (UniKL MIIT) and Université de La Rochelle, France
Venue:
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Year:
2012

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Abstract

This research work is based on the location prediction of wireless nodes with the terrains/clutters considerations. Multi-condition Bayesian decision theory is applied for precision in selected locations. Currecnt research is the continution of our previous research work in which twelve terrains were proposed based on the atmospharic atteunation. In the first phase of paper, basic parameters such as receive signal strength and available signal strength are calculated by using terrain/clutter considerations. Secondly, geomatric approach is used to calculate angle of arrival. Finally, multi-condition bayesian decision theory is used to precise the calculated results. Three posterior probabilities, the angle error rate (e), overlapping coverage area (Ω) and the terrains/clutters error rate (Ć) are used with the Bayesian decision theory for the most probable location of wireless node. Results show that 60%- 80% accuracy could be achived if proper terrain defination and multi-condition bayesian decision theory is followed.