NDLI: C41. Multisensor estimate fusion based on Bayesian minimum mean square error criterion

Content Provider	IEEE Xplore Digital Library
Author	Aziz, A.M. Zaher, N.
Copyright Year	2012
Description	Author affiliation: Electronics and Communications Department, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport, Cairo, Egypt (Aziz, A.M.; Zaher, N.)
Abstract	Estimate fusion combines data from distributed sensors, monitor an entity, to obtain an accurate estimate of the entity's. It takes advantages of redundancy and diversity present in the measured data. If the measured data from multiple sensors is correctly combined, then the fused sensor data has better accuracy. This paper addresses the problem of estimate fusion, based on Bayesian minimum mean square error criterion, using measurement from multiple sensors. The results show that the performance of the fused measurements may perform worse than the performance of the individual sensor measurements. The best performance of the fused measurements occurs when the sensors have the same accuracies. The performance of the fused measurements is worse than the performance of the best accurate sensor when the sensors' accuracies vary widely. In this case, adopting the best accurate sensor is recommenced and estimate fusion is not recommended.
Starting Page	503
Ending Page	514
File Size	640459
Page Count	12
File Format	PDF
ISBN	9781467318846
e-ISBN	9781467318877
DOI	10.1109/NRSC.2012.6208559
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-10
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensor fusion Aircraft Sea measurements Sensor phenomena and characterization Surveillance Multiple Sensors Estimate Fusion Bayesian Minimum Mean Square Error
Content Type	Text
Resource Type	Article

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