混合信号的调制识别方法基于循环频谱投影
Weichao Yang1, Ke Ren2, Yu Du1
1National Key Laboratory of Science and Technology on Space Microwave, China Academy of Space Technology (Xi'an), Xi'an, 710100, China.
Scientific reports
|December 5, 2023
概括
这项研究引入了一种新的方法,用于识别使用循环光谱投影和深度神经网络的混合信号. 该技术有效地识别混合信号,即使在杂的环境中,也具有高精度.
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:
- 复杂的电磁环境导致各种调制类型的混合信号.
- 现有的混合信号识别方法缺乏适应性.
- 混合信号的调制识别是现代通信的一个关键挑战.
研究的目的:
- 提出一种用于混合信号调制识别的新且可适应的方法.
- 利用循环频谱特性和深度神经网络进行增强的识别.
- 在不同的信号条件下克服现有方法的局限性.
主要方法:
- 理论推导证明循环频谱用于信号识别的可行性.
- 使用2D循环光谱的灰度投影作为识别表示.
- 应用非线性断片映射和定向伪聚类来增强光谱图像.
- 使用深度神经网络进行抽象特征提取和识别.
主要成果:
- 拟议的方法证明了对噪声的稳定性,在信号对噪声比率>=0dB时达到超过95%的平均识别率.
- 该技术表现出很好的适应性,适应信号符号速率的变化.
- 该方法对混合信号之间的能量比率变化具有弹性.
结论:
- 开发的方法有效地通过循环光谱投影和深度神经网络识别混合信号.
- 与现有技术相比,这种方法在适应性和稳定性方面提供了显著的改进.
- 该方法为复杂信号环境中的调制识别提供了可靠的解决方案.
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