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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2018, Vol. 39 
