Multiple sensor data fusion algorithm based on fuzzy sets and statistical theory

Abstract

Multiple sensor information fusion technology originated from the military. It has developed into a very active and popular field of defense research. It is also a high-level universal key technology, which has attracted attention in many disciplines and fields. Many countries, including China, have listed them on the research list. The purpose of this paper is to study multiple sensor data fusion through fuzzy sets and statistical theory. According to the scholars’ research results at home and abroad, proposed a new evidence synthesis algorithm. The algorithm combines the advantages of modifying the original evidence and modifying the comprehensive rules. By comparing the accuracy of 100 sensor data in multiple sensors and single sensors, the consistency information and conflict information between the evidences are, mined and comprehensively considered the consistency information and conflict information between the evidences,, and analyzed the evidence empirically. Considered ENCE in the weight distribution of conflict evidence fully. By comparing the results of multiple sets of experiments, established multiple sensor data fusion algorithm based on fuzzy sets and statistical theory. Record experimental data and analyze the experimental results. The experimental results show that compared with other methods, the method can reflect the credibility of the evidence more objectively, the convergence speed is faster, and the fusion result is more in line with the actual situation. The experimental results show that the fusion algorithm based on the best fusion set and the new integrated method of conflict evidence can be used as the core algorithm of local fusion center and global fusion center in the fusion system respectively, and can also be used as the secondary fusion model of the fusion system.