Infrared multi-sensor fusion recognition method based on ISVM-DS

被引：0
|
作者：
Wu Y. [1 ]
Wang C. [1 ]
Wang J. [2 ]
Li X. [2 ]
机构：
[1] College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing
[2] Beijing Institute of Electronic System Engineering, Beijing
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2024年 / 46卷 / 05期
关键词：
ballistic target recognition; Dempster-Shafer (D-S) evidence theory; multi-sensor fusion; support vector machine (SVM);
D O I：
10.12305/j.issn.1001-506X.2024.05.10
中图分类号：
学科分类号：
摘要：
In the middle part of the ballistic trajectory, the target is a group of targets, including warheads, decoys, and fragments. Moreover, due to the long distance from the sensor, the infrared imaging of the target is a point target with less available information. Therefore, a single infrared sensor is often difficult to meet the recognition requirements, which means that multiple sensors need to be fused to complete the recognition task. In response to the fusion recognition problem of infrared multiple sensors, a fusion recognition method based on increment support vector machine-Dempster-Shafer (ISVM-DS) evidence theory is proposed. Firstly, the support vector data description (SVDD) model of infrared features of multiple band sensors is trained, and the shell vector is generated and the ISVM model is trained. Then the posterior probability of the ISVM model is used to generate basic probability assignment (BPA). Finally, the D-S evidence theory is used to fuse the BPA of multiple evidences and output classification results. Experimental results show that the proposed method can effectively improve the accuracy of target recognition. © 2024 Chinese Institute of Electronics. All rights reserved.
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页码：1555 / 1560
页数：5
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