Classifying aircraft based on sparse recovery and deep-learning

Classifying aircraft based on sparse recovery and deep-learning

A hybrid CS-DL method for aircraft classification in complex electromagnetic environment is introduced. To classify aircraft from interfered radar echoes, the authors propose a novel classification method based on compressed sensing (CS) and deep-learning (DL). After recovering the spectrum polluted...

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Bibliographic Details
Main Authors: Wang Wenying, Wei Yao, Zhen Xuanxuan, Yu Hui, Wang Ruqi
Format: Article
Language:English
Published: Wiley 2019-10-01
Series:The Journal of Engineering
Subjects:
jamming
signal classification
learning (artificial intelligence)
feature extraction
neural nets
radar cross-sections
aerospace computing
interference (signal)
deep-learning
sparse auto-encoder
correct classification rate
sparse recovery
hybrid cs-dl
aircraft classification
complex electromagnetic environment
interfered radar echoes
novel classification method
compressed sensing
jamming signals
modulation feature extraction
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0633

Internet

https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0633

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