电波科学学报2025，Vol.40Issue(1)：58-62,5.DOI:10.12265/j.cjors.2024225
基于电磁仿真和机器学习的快速目标成像模型
A fast target imaging model based on electromagnetic simulation and machine learning
黄猛 1李少猛 1王玉菊 1王青山 2代维凯 1张思维 2李典2
作者信息
- 1. 中国人民解放军 91977 部队,北京 102249
- 2. 中国船舶集团有限公司第七一四研究所,北京 100101
- 折叠
摘要
Abstract
With the rapid advancement of radar technology,traditional inverse synthetic aperture radar(ISAR)image simulation methods based on electromagnetic(EM)scattering calculations often face the challenge of high time costs,making it difficult to generate high-resolution ISAR image samples in real time.To address the issue of low efficiency in constructing image sample datasets for complex targets,a machine learning-based model for fast ISAR image prediction is proposed.This model uses a small amount of ISAR echo data as the input for EM calculations of complex targets.Data augmentation techniques are employed to increase dataset diversity,and a dynamic weighted ensemble method is applied to integrate three commonly used regression models:linear regression,support vector machine(SVM),and random forest.The proposed ensemble model can rapidly predict ISAR echo data,reducing the number of EM simulations required and significantly improving the efficiency of sample generation.Experimental results demonstrate that the model can accurately predict all the data needed to generate images using only a small amount of echo data,achieving an overall efficiency improvement of approximately 80%.As the complexity and resolution of the target increase,the time required for simulation methods will increase significantly.At this point,our proposed model will demonstrate greater advantages.关键词
逆合成孔径雷达(ISAR)图像/电磁(EM)散射计算/机器学习/集成方法/数据增强Key words
inverse synthetic aperture radar(ISAR)imaging/EM scattering computation/machine learning/ensemble method/data enhancement分类
物理学引用本文复制引用
黄猛,李少猛,王玉菊,王青山,代维凯,张思维,李典..基于电磁仿真和机器学习的快速目标成像模型[J].电波科学学报,2025,40(1):58-62,5.
