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Sensors 2017, 17(7), 1575; https://doi.org/10.3390/s17071575

A Reliability-Based Method to Sensor Data Fusion

School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
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Received: 21 May 2017 / Revised: 1 July 2017 / Accepted: 3 July 2017 / Published: 5 July 2017
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Abstract

Multi-sensor data fusion technology based on Dempster–Shafer evidence theory is widely applied in many fields. However, how to determine basic belief assignment (BBA) is still an open issue. The existing BBA methods pay more attention to the uncertainty of information, but do not simultaneously consider the reliability of information sources. Real-world information is not only uncertain, but also partially reliable. Thus, uncertainty and partial reliability are strongly associated with each other. To take into account this fact, a new method to represent BBAs along with their associated reliabilities is proposed in this paper, which is named reliability-based BBA. Several examples are carried out to show the validity of the proposed method. View Full-Text
Keywords: sensor data fusion; Dempster–Shafer evidence theory; Gaussian distribution; reliability-based BBA sensor data fusion; Dempster–Shafer evidence theory; Gaussian distribution; reliability-based BBA
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Jiang, W.; Zhuang, M.; Xie, C. A Reliability-Based Method to Sensor Data Fusion. Sensors 2017, 17, 1575.

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