雷达科学与技术2025，Vol.23Issue(5)：473-481,490,10.DOI:10.3969/j.issn.1672-2337.2025.05.001
基于VAE-WGAN的海杂波幅度-时频联合生成建模
Joint Magnitude-Time-Frequency Generative Modeling of Sea Clutter Using VAE-WGAN
摘要
Abstract
To address the limitations of traditional statistical models in simulating the time-frequency characteris-tics of sea clutter,a sea clutter data generation method based on an enhanced generative adversarial network(GAN)is proposed in this paper.The complex sea clutter is decomposed into amplitude and time-frequency components,which are separately fed into a variational autoencoder-Wasserstein generative adversarial network(VAE-WGAN)for train-ing.The outputs are then integrated to synthesize complex signals with both amplitude and phase characteristics.To en-hance the model performance,a gradient penalty mechanism is introduced to constrain the Lipschitz continuity of the discriminator,effectively mitigating the mode collapse.A self-attention module is incorporated to strengthen the model's ability to capture localized strong scattering features,such as sea spikes,significantly improving the spatiotemporal cor-relation of generated signals.Experiments cover sea states 2～5,with three datasets of dimensions[64,64],[128,128],and[256,256]constructed for each sea state.Twelve cross-validation trials demonstrate that the synthetic data exhibit high consistency with measured data in amplitude distribution,normalized spectrum,temporal correlation,and time-fre-quency characteristics.These results validate the model's generalization capability across varying sea states and multi-scale temporal scenarios.关键词
海杂波/生成对抗网络/时频特性/数据增强Key words
sea clutter/generative adversarial network/time-frequency characteristics/data enhancement分类
电子信息工程引用本文复制引用
刘宁波,刘新亮,董云龙,丁昊,关键,孙殿星..基于VAE-WGAN的海杂波幅度-时频联合生成建模[J].雷达科学与技术,2025,23(5):473-481,490,10.基金项目
国家自然科学基金(No.62388102,62101583) （No.62388102,62101583）
泰山学者工程(No.tsqn2002211246) （No.tsqn2002211246）
