RCS Statistical Feature Extraction for Space Target Recognition Based on Bi-LSTM
Author:
Affiliation:
1. Fudan University,Key Laboratory for Information Science of Electromagnetic Waves (MoE), School of Information Science and Technology,Shanghai,China,200433
Funder
National Natural Science Foundation of China
Natural Science Foundation of Shanghai
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10281394/10281399/10281917.pdf?arnumber=10281917
Reference9 articles.
1. Fusion Recognition of Space Targets With Micromotion
2. Feature reduction and selection for EMG signal classification
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4. Micro-motion forms classification of space cone-shaped target based on convolution neural network;xu;The Applied Computational Electromagnetics Society Journal (ACES),2020
5. Space Precession Target Classification Based on Radar High-Resolution Range Profiles
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1. Space Target Recognition Based on RCS Feature Extraction Using Relative Position Matrix;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07
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