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- Title
An Intelligent Denoising Method for Jamming Pattern Recognition under Noisy Conditions.
- Authors
Changhua YAO; Yang LI; Yufan CHEN; Kaixin CHENG
- Abstract
Accurate identification of jamming patterns is a crucial decision-making basis for anti-jamming in wireless communication systems. Current works still face challenges in fully considering the substantial influence of environmental noise on identification performance. To address the issue, this paper proposes an automatic threshold denoising-based deep learning model. The proposed method aims to mitigate the impact of noise on recognition performance within the feature space. Considering the challenges posed by nonlinear transformations in deep denoising, a shallow denoising approach based on deep learning is proposed. By constructing a dataset of 12 jamming patterns under noisy conditions, the proposed method exhibits excellent recognition performance and maintains a low computational cost.
- Subjects
PATTERN recognition systems; DEEP learning; CONVOLUTIONAL neural networks; WIRELESS communications; RADAR interference; IDENTIFICATION
- Publication
Radioengineering, 2024, Vol 33, Issue 2, p322
- ISSN
1210-2512
- Publication type
Article
- DOI
10.13164/re.2024.0322