基于混合特征和合奏学习的无线电信号调制识别方法:用于雷达和干扰信号
Yu Zhou1,2, Ronggang Cao1,2,3, Anqi Zhang1,2
1School of Electrical and Mechanical, Beijing Institute of Technology, Beijing 100081, China.
Sensors (Basel, Switzerland)
|August 10, 2024
概括
这项研究引入了一种先进的无线电信号调制识别方法,以对抗雷达干扰和干扰. 集体学习方法提高了检测性能,即使在具有挑战性的低信号噪声比条件下.
科学领域:
- 电气工程 电气工程
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 雷达检测性能因主动干扰和干扰而降低.
- 准确的信号识别对于有效的干扰取消策略至关重要.
研究的目的:
- 提出一种新的无线电信号调制识别方法.
- 通过改进的信号识别来增强雷达反干扰能力.
主要方法:
- 使用集体学习堆叠算法与元特征增强.
- 采用随机森林,K-最近的邻居和高斯素朴的贝叶斯作为基础学习者.
- 集成的多域信号特征:时间 (模糊,斜率,Hjorth参数),频率 (光谱) 和碎形 (碎形维度).
主要成果:
- 与现有的分类技术相比,拟议的方法显示出更高的性能.
- 实现了七种常见的雷达和主动干扰信号类型的有效识别.
- 在低信号/噪声比和少数拍摄学习场景下验证的性能.
结论:
- 开发的调制识别方法在存在干扰时显著改善了雷达信号检测.
- 这种方法对于实际的防干扰应用来说是强大而有效的,即使数据有限且信号质量差.
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