针对甚低频通信带宽窄、信道噪声非高斯的特性，对一种超窄带调制方式在甚低频通信中的应用进行研究，通过分析甚低频通信环境下的主要噪声和干扰特性，提出一种解调方法，该方法结合非线性削波算法和基于反向传播算法的神经网络，利用激活函数的非线性特性对非高斯信道下的干扰进行拟合，解决了传统解调算法在低信噪比的脉冲噪声环境失效的问题。Matlab仿真表明，该解调方法具有较高的鲁棒性，经过训练后的网络在低信噪比的脉冲噪声信道、脉冲噪声与高斯白噪声混合信道下均优于传统算法6 dB以上。
To address the narrow bandwidth and non-Gaussian channel noise characteristics of Very Low Frequency (VLF) communication systems, this paper investigates the application of a kind of ultra narrow band modulation technique. By analyzing the primary noise and interference features in VLF communication environments, a demodulation method that combines a nonlinear clipping algorithm with a neural network based on the Back Propagation (BP) algorithm is proposed. Leveraging the nonlinear activation functions of the neural network, this approach effectively models and mitigates interference in non-Gaussian channels, overcoming the limitations of conventional demodulation algorithms under low signal-to-noise ratio impulsive noise conditions. Simulation results based on Matlab demonstrate that the proposed method exhibits superior robustness compared to traditional algorithms, achieving performance improvements exceeding 6 dB in both impulsive noise channel and mixed impulsive and white Gaussian noise channels.
2026,48(7): 95-100 收稿日期：2025-8-26
DOI：10.3404/j.issn.1672-7649.2026.07.016
分类号：U675.75
作者简介：谭秋玥(1994-),女,硕士,工程师,研究方向为信号处理及通信抗干扰、下一代通信技术等
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