Sensors 2013, 13(12), 17193-17221; doi:10.3390/s131217193
Article

Sensor Reliability Evaluation Scheme for Target Classification Using Belief Function Theory

1,2,* email, 1email and 2,3email
1 Tsinghua National Laboratory for information Science and Technology (TNList), Department of Automation, Tsinghua University, Beijing 100084, China 2 Navy Academy of Armament, Beijing 102249, China 3 Bejing University of Aeronautics and Astronautics, Beijing 100191, China
* Author to whom correspondence should be addressed.
Received: 28 October 2013; in revised form: 4 December 2013 / Accepted: 8 December 2013 / Published: 13 December 2013
(This article belongs to the Section Sensor Networks)
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Abstract: In the target classification based on belief function theory, sensor reliability evaluation has two basic issues: reasonable dissimilarity measure among evidences, and adaptive combination of static and dynamic discounting. One solution to the two issues has been proposed here. Firstly, an improved dissimilarity measure based on dualistic exponential function has been designed. We assess the static reliability from a training set by the local decision of each sensor and the dissimilarity measure among evidences. The dynamic reliability factors are obtained from each test target using the dissimilarity measure between the output information of each sensor and the consensus. Secondly, an adaptive combination method of static and dynamic discounting has been introduced. We adopt Parzen-window to estimate the matching degree of current performance and static performance for the sensor. Through fuzzy theory, the fusion system can realize self-learning and self-adapting with the sensor performance changing. Experiments conducted on real databases demonstrate that our proposed scheme performs better in target classification under different target conditions compared with other methods.
Keywords: information fusion; sensor reliability; belief function theory; discounting factor; target classification

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MDPI and ACS Style

Zhu, J.; Luo, Y.; Zhou, J. Sensor Reliability Evaluation Scheme for Target Classification Using Belief Function Theory. Sensors 2013, 13, 17193-17221.

AMA Style

Zhu J, Luo Y, Zhou J. Sensor Reliability Evaluation Scheme for Target Classification Using Belief Function Theory. Sensors. 2013; 13(12):17193-17221.

Chicago/Turabian Style

Zhu, Jing; Luo, Yupin; Zhou, Jianjun. 2013. "Sensor Reliability Evaluation Scheme for Target Classification Using Belief Function Theory." Sensors 13, no. 12: 17193-17221.

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