A fusion approach based on evidential reasoning rule considering the reliability of digital quantities

Abstract

As a typical multi-sensor fusion technology, the evidential reasoning (ER) rule has been widely used in evaluation, decision, and classification tasks. Current researches on the ER rule tend to fuse objects of the same type, such as the unquantized analog quantity. However, the fusion of unquantized analog quantity and quantized digital quantity is more common in engineering, but has received minimal attention. Given the characteristics of the ER rule, the biggest challenge imposed by this fusion is to consider the reliability of digital quantity reasonably. In this paper, a new fusion approach of digital and analog quantity based on the ER rule is proposed. In order to improve the fusion accuracy, the combination of quantization error and external noise is adopted to measure the reliability of digital quantity. On this basis, the digital and analog quantities are fused together according to the ER rule. To further explore the intrinsic mechanism of the proposed approach, a detailed performance analysis is conducted to study the variation law of evidence reliability and fusion results. Finally, a numerical example and a case study are intended to demonstrate the effectiveness of the proposed approach.