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Open AccessArticle

Paradox Elimination in Dempster–Shafer Combination Rule with Novel Entropy Function: Application in Decision-Level Multi-Sensor Fusion

Department of Mechanical and Energy Engineering, IUPUI, Indianapolis, IN 46224, USA
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Author to whom correspondence should be addressed.
Sensors 2019, 19(21), 4810; https://doi.org/10.3390/s19214810
Received: 10 October 2019 / Revised: 28 October 2019 / Accepted: 30 October 2019 / Published: 5 November 2019
(This article belongs to the Collection Multi-Sensor Information Fusion)
Multi-sensor data fusion technology in an important tool in building decision-making applications. Modified Dempster–Shafer (DS) evidence theory can handle conflicting sensor inputs and can be applied without any prior information. As a result, DS-based information fusion is very popular in decision-making applications, but original DS theory produces counterintuitive results when combining highly conflicting evidences from multiple sensors. An effective algorithm offering fusion of highly conflicting information in spatial domain is not widely reported in the literature. In this paper, a successful fusion algorithm is proposed which addresses these limitations of the original Dempster–Shafer (DS) framework. A novel entropy function is proposed based on Shannon entropy, which is better at capturing uncertainties compared to Shannon and Deng entropy. An 8-step algorithm has been developed which can eliminate the inherent paradoxes of classical DS theory. Multiple examples are presented to show that the proposed method is effective in handling conflicting information in spatial domain. Simulation results showed that the proposed algorithm has competitive convergence rate and accuracy compared to other methods presented in the literature. View Full-Text
Keywords: Dempster–Shafer evidence theory (DST); uncertainty measure; novel belief entropy; multi-sensor data fusion; decision-level sensor fusion Dempster–Shafer evidence theory (DST); uncertainty measure; novel belief entropy; multi-sensor data fusion; decision-level sensor fusion
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MDPI and ACS Style

Khan, M.N.; Anwar, S. Paradox Elimination in Dempster–Shafer Combination Rule with Novel Entropy Function: Application in Decision-Level Multi-Sensor Fusion. Sensors 2019, 19, 4810. https://doi.org/10.3390/s19214810

AMA Style

Khan MN, Anwar S. Paradox Elimination in Dempster–Shafer Combination Rule with Novel Entropy Function: Application in Decision-Level Multi-Sensor Fusion. Sensors. 2019; 19(21):4810. https://doi.org/10.3390/s19214810

Chicago/Turabian Style

Khan, Md N.; Anwar, Sohel. 2019. "Paradox Elimination in Dempster–Shafer Combination Rule with Novel Entropy Function: Application in Decision-Level Multi-Sensor Fusion" Sensors 19, no. 21: 4810. https://doi.org/10.3390/s19214810

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