JOURNAL ARTICLE

Research on Improved Multi-Sensor Data Fusion Algorithm Based on D-S Evidence Theory

Junsuo QuXing CaiHaonan Shi

Year: 2021 Journal:   2021 4th International Conference on Artificial Intelligence and Pattern Recognition Pages: 486-493

Abstract

The data fusion of multi-sensor enhances the intrinsic relationship of data between sensors, reduces the workload of information processing, and will not miss the important information features. This paper points out the main problems in the application of D-S evidence theory, analyzes and compares the existing improved methods. When the evidence conflict is large, the traditional D-S evidence theory synthesis formula is inconsistent with the actual situation and the result is invalid. The priority factor is introduced to reallocate the basic probability assignment of the evidence conflict part. And the method is used for map construction simulation. From the constructed ring map, it can be seen that the obstacle points of each decision are very close to the obstacle points in the simulation. The reliability and accuracy of the method of introducing priority factor in drawing construction are explained.

Keywords:
Obstacle Sensor fusion Reliability (semiconductor) Computer science Workload Information fusion Algorithm Data mining Factor (programming language) Artificial intelligence

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Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Image Processing and 3D Reconstruction
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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