Design of fuzzy set-based deep fusion algorithm for multi-sensor data

Accompanied by the rapid development of sensors, Internet of Things technology, multi-sensor systems have been more widely used, people can obtain the amount of information and the type of information is also more and more rich, how to effectively utilize and deal with the information obtained is particularly critical, in which the data fusion technology plays a crucial role. In this paper, the basic principle of multi-sensor data fusion is introduced in detail, and the classical application of fuzzy sets in data fusion is summarized based on fuzzy theory. In order to further explore the application of multi-sensor fusion technology in related aspects, according to the existing research methods exist in the target conflict problem this paper puts forward the fusion method based on improved fuzzy weighting, and at the same time, according to the existing theory combined with simulation experiments to verify the effect of data fusion in this paper. In the experiment, the final fusion weighted values of nodes 1~3 are 0.213, 0.291 and 0.496 respectively, and the fusion effect of this paper’s method is good. And through the effect comparison, the recognition success rate of this paper’s method in target detection is 82.6%, which verifies that this paper’s data fusion method based on fuzzy set has better feasibility, and also verifies the effectiveness of the optimization method proposed in this paper.