JOURNAL ARTICLE

Automatic Classification of Radar Signals Using CNN

Seok‐Jun HongYearn-Gui YiJeil JoSang‐Gil LeeBo-Seok Seo

Year: 2019 Journal:   The Journal of Korean Institute of Electromagnetic Engineering and Science Vol: 30 (2)Pages: 132-140   Publisher: The Korean Institute of Electromagnetic Engineering and Science

Abstract

In this paper, we propose a classification method for radar signals depending on the type of threat by applying machine learning to parameter data of radar signals . Currently, the army uses a library of mapping relations between the parameters and the types of threat to recognize threat signals. This approach has certain limitations when classifying signals and recognizing new types of threat or types of threat that do not exist in the current libraries. In this paper, we propose an automatic radar signal classification method depending on the type of threat that uses only parameter data without a library. A convolutional neural network is used as the classifier and machine learning is applied to train the classifier. The proposed method does not use a library, and hence, can classify threat signals that are new or do not exist in the current library.

Keywords:
Radar Convolutional neural network Computer science Classifier (UML) Artificial intelligence Pattern recognition (psychology) Machine learning Artificial neural network Data mining Telecommunications

Metrics

2
Cited By
0.63
FWCI (Field Weighted Citation Impact)
5
Refs
0.80
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced SAR Imaging Techniques
Physical Sciences →  Engineering →  Aerospace Engineering
Gait Recognition and Analysis
Physical Sciences →  Engineering →  Biomedical Engineering
Radar Systems and Signal Processing
Physical Sciences →  Engineering →  Aerospace Engineering

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