电波科学学报2025，Vol.40Issue(2)：252-260,9.DOI:10.12265/j.cjors.2024121
基于多头自注意力扩散模型的雷达图像海杂波抑制
Sea clutter suppression for radar images based on multi-head self-attention diffusion model
摘要
Abstract
To address the severe interference of sea clutter on radar echo signals,a sea clutter suppression for radar images based on a multi-head self-attention diffusion model is proposed.Based on the diffusion model,a multi-head self-attention diffusion network model(MHA-DNet)is developed by integrating a multi-head self-attention mechanism.which facilitates feature extraction and learning of the characteristics of sea clutter.In this study,diverse targets of ocean clutter time-frequency images are simulated based on the IPIX Radar clutter dataset,resulting in a large-scale and stochastic image dataset.This approach enhances the model generalization ability,making it more robust.On the newly proposed peak signal-to-noise ratio structural similarity index(P-S)evaluation metrics in this paper,MHA-DNet shows a high performance improvement of 4%compared with the traditional convolutional method,and 1.1%compared with the GAN adversarial network method,and even compared with the original diffusion model,MHA-DNet demonstrates a 0.2%advantage,which verifies that the method proposed in this paper has a certain degree of effectiveness in the sea clutter suppression.关键词
海杂波抑制/扩散模型/深度学习/多头自注意力(MHA)机制/海杂波时频图Key words
sea clutter suppression/diffusion model/deep learning/multi-head self-attention(MHA)mechanism/sea clutter time-frequency diagram分类
电子信息工程引用本文复制引用
马迪,杜晓林,陈小龙,荣尧,于爽,万训杨..基于多头自注意力扩散模型的雷达图像海杂波抑制[J].电波科学学报,2025,40(2):252-260,9.基金项目
国家自然科学基金(61801415,62222120,62101482) （61801415,62222120,62101482）
云南省统计建模与数据分析重点实验室开放课题(SMDAYB2023002) （SMDAYB2023002）
云南省基础研究专项(青年项目)(202301AU070213) （青年项目）
