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2020年 第21卷 第11期

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《信息与电子工程前沿（英文）》 >> 2020年 第21卷 第11期 doi: 10.1631/FITEE.1900590

An artificial intelligence enhanced star identification algorithm

Affiliation(s): School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027, China; Department of Mechanical and Aerospace Engineering, University at Buffalo, State University of New York, Amherst, NY 14260-4400, USA; less

收稿日期： 2019-10-30 录用日期： 2020-11-13 发布日期： 2020-11-13
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An artificial intelligence enhanced algorithm is proposed for s in mode. A model based on Vgg16 is used in the artificial intelligence algorithm to classify star images. The training dataset is constructed to achieve the networks’ optimal performance. Simulation results show that the proposed algorithm is highly robust to many kinds of noise, including position noise, magnitude noise, false stars, and the tracker’s angular velocity. With a deep , the identification accuracy is maintained at 96% despite noise and interruptions, which is a significant improvement to traditional pyramid and grid algorithms.

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