Duong, V.M. and Nguyen, T.P. and Phan, N.G. (2024) Advanced Method for Polyphase Coded Radar Signal Classification and Recognition Based on Deep Learning. Lecture Notes in Networks and Systems, 1077 L. pp. 238-247. ISSN 23673370
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An advanced method based on modified wavelet transform and deep learning was proposed to reduce training time and improve the recognition accuracy of polyphase-coded radar signals in low signal-to-noise ratios. The proposed method includes two stages. In the first step, the feature parameters of polyphase-coded radar signals (Barker, Frank, P1, Px, Zadoff-Chu) are extracted. Then, the classification and recognition of polyphase-coded radar signals are implemented using Deep learning. The tested results show that the proposed method exceeds the existing methods based on machine learning and artificial intelligence in terms of time training and accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
| Item Type: | Article |
|---|---|
| Divisions: | Offices > Office of International Cooperation |
| Identification Number: | 10.1007/978-981-97-5504-2₂₈ |
| Uncontrolled Keywords: | Adversarial machine learning; Contrastive Learning; Deep learning; Radar target recognition; Signal to noise ratio, Classification and recognition; Deep learning; Feature parameters; Low signal-to-noise ratio; Polyphase-coded radar signals; Radar signal classifications; Recognition accuracy; Signal recognition; Training time; Wavelets transform, Wavelet transforms |
| Additional Information: | Conference of International Conference on Intelligent Systems and Networks, ICISN 2024 ; Conference Date: 22 March 2024 Through 23 March 2024; Conference Code:318189 |
| URI: | http://eprints.lqdtu.edu.vn/id/eprint/11370 |
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