电波科学学报2024，Vol.39Issue(6)：1146-1153,8.DOI:10.12265/j.cjors.2023304
复杂时空场景下的海杂波幅度分布一体化预测方法
An integrated prediction method for sea clutter amplitude distribution in complex spatio-temporal scenarios
摘要
Abstract
The characteristics of sea clutter undergo changes influenced by the spatial-temporal variations in marine meteorological conditions,exhibiting significant spatial-temporal non-uniformity.This severely impacts the detection capability of radar systems in different maritime domains.In this study,considering the description of sea clutter amplitude distribution relies on both distribution types and parameters,this paper proposes an integrated prediction method for sea clutter amplitude distribution based on multi-task parallel learning using deep learning technology.To address the issue of negative output values in parameter prediction,a loss function that suppresses negative values is introduced.This enables parallel prediction of sea clutter amplitude distribution types and parameters.Through training and testing on a dataset from the South China Sea comprising S-band sea clutter data and spatio-temporally corresponding marine meteorological parameter data,the results indicate that this approach can effectively predict sea clutter amplitude distribution types and parameters in spatio-temporal scenarios influenced by changing marine meteorological conditions.This method facilitates the prediction of sea clutter amplitude distribution characteristics in large-scale maritime regions with varying spatio-temporal conditions.关键词
海杂波/幅度分布/海洋气象要素/复杂时空场景/深度学习/一体化预测Key words
sea clutter/amplitude distribution/oceanic meteorological element/complex spatio-temporal scenarios/deep learning/integrated prediction method分类
信息技术与安全科学引用本文复制引用
华志恒,张金鹏,殷波,王艺卫,张玉石..复杂时空场景下的海杂波幅度分布一体化预测方法[J].电波科学学报,2024,39(6):1146-1153,8.基金项目
国家自然科学基金(62271457) （62271457）
