Uncertainty evaluation for a Dezert-Smarandache theory-based localization problem

Dezert-Smarandache theory (DSmT) is selected as the fusion method in a decision making system. To compare sensor fusion results, an uncertainty analysis is performed at each level of the decision making system. The supervision is based on the Generalized Aggregated Uncertainty (GAU) measure which is...

Full description

Saved in:
Bibliographic Details
Published in:International journal of general systems 2014-08, Vol.43 (6), p.610-632
Main Authors: Khodabandeh, M., Shahri, A.M.
Format: Article
Language:English
Subjects:
Cameras
data fusion
Decision making
Dezert-Smarandache theory
hierarchical decision making and camera's image
Localization
Position (location)
Sensors
Uncertainty
uncertainty measurement
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Dezert-Smarandache theory (DSmT) is selected as the fusion method in a decision making system. To compare sensor fusion results, an uncertainty analysis is performed at each level of the decision making system. The supervision is based on the Generalized Aggregated Uncertainty (GAU) measure which is a generalization of Aggregated Uncertainty measure, whereas it is applicable for DSmT results. This measure helps to make decisions on better choice of combinations of sensors or methods of fusion. As an experimental study, localization of an object using cameras' images is selected. Classic DSmT and hybrid DSmT by using extra knowledge, is applied and then uncertainty evaluation is carried out by the GAU uncertainty measure. The final decision in the presented framework has uncertainty less than each sensor's measurement. By this method, more accurate and less uncertain results in localizing the object with high conflict sensory data are generated.
ISSN:0308-1079
1563-5104
DOI:10.1080/03081079.2014.896353