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Analysis of Measurement Message Fusion and Uncertainty Treatment Based on Possibility Theory |
YU Xue-feng,YU Jie,ZHANG Hong-qing |
Unit 63870, PLA, Huayin, Shaanxi 714200, China |
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Abstract Deal with the question of measurement message fusion and uncertainty treatment, a method using conditional possibility distribution to derive the posteriori information about the measurement was proposed. An approach to measurement message fusion and uncertainty treatment in terms of random-fuzzy variables (RFVs) possibility distributions instead of probability distributions was presented. A simple measurement example was also considered to prove the usefulness and effectiveness of the proposed method. The results show that, based on possibility theory, it is possible to obtain a more accurate posteriori estimate of the measurement combining with the reliable measurement priori knowledge.
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Received: 17 November 2016
Published: 29 December 2017
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