信号处理2025，Vol.41Issue(6)：1040-1054,15.DOI:10.12466/xhcl.2025.06.004
高分辨雷达基于智能语义分割的黎曼流形复杂环境杂波抑制方法
High-Resolution Radar Clutter Suppression Method on Riemannian Manifold Based on Intelligent Semantic Segmentation in Complicated Environments
摘要
Abstract
Radar detection of low-altitude targets,such as migrating biological entities and unmanned aerial vehicles(UAVs),is heavily impacted by complex clutter environments,resulting in increased missed detections and false alarms.Addressing this challenge requires effective clutter suppression methods.This paper introduces a clutter suppres-sion method based on intelligent semantic segmentation on the Riemannian manifold,designed to handle high-resolution clutter in complicated environments.In such scenarios,low-altitude weather clutter and ground clutter are superim-posed,with clutter types and characteristics exhibiting spatial variability.The proposed method employs intelligent se-mantic segmentation using a U-net architecture to distinguish various clutter types in the range-Doppler domain.This segmentation identifies clutter regions and informs subsequent clutter suppression strategies.A clutter semantic segmen-tation dataset,constructed using real rain and ground clutter data collected by a high-resolution phased array radar,was used to train the intelligent segmentation network.The semantic segmentation process categorizes high-resolution radar echoes into subbands in the Doppler dimension based on clutter type.For each clutter region,the clutter power spectral density(PSD)is estimated using the geometric mean of reference cell samples on the Riemannian manifold.Reference cells are selected based on segmentation results,ensuring that samples with consistent time-frequency characteristics are used for estimation.Finally,an adaptive clutter suppression filter is constructed using the clutter PSD to achieve effec-tive suppression.The proposed method is validated using real high-resolution clutter data obtained under diverse weather conditions and radar positions.Experimental results from two scenarios—real clutter data with simulated targets and real data containing both clutter and targets—demonstrate that the method effectively suppresses clutter in complex,multi-type environments.This approach significantly enhances the signal-to-clutter ratio of targets,improving detection perfor-mance in challenging conditions.关键词
高分辨杂波/杂波语义分割/杂波抑制/黎曼流形Key words
high-resolution clutter/clutter semantic segmentation/clutter suppression/Riemannian manifold分类
信息技术与安全科学引用本文复制引用
严雨佳,胡程,蔡炯,王廉钧,杨翰东,王锐..高分辨雷达基于智能语义分割的黎曼流形复杂环境杂波抑制方法[J].信号处理,2025,41(6):1040-1054,15.基金项目
国家自然科学基金(624B2026) The National Natural Science Foundation of China(624B2026) （624B2026）
