针对船舶目标辐射噪声周期性平稳特征提取问题，本文进行船舶目标辐射噪声周期性平稳特征提取方法研究。利用循环谱提取船舶目标辐射噪声周期性平稳的线谱特征；通过经典及现代数字信号处理手段，利用船舶目标辐射噪的循环谱、循环谱频域相干性、循环频率在循环谱中的分布规律，提出一种局部特征-循环相干性线谱周期性平稳特征提取方法，提取船舶目标辐射噪声周期性平稳特征，有效提高绝对弱信号循环谱的循环线谱的信噪比。通过仿真及试验数据验证，本文提出的特征提取算法，对于弱目标、弱频率分量的特征提取相较于传统方法具备有效性，所提方法可为船舶目标识别提供有效的技术手段。
Focusing on the extraction of periodic-stationary features in ship target radiated noise, this paper investigates methods for extracting such features by utilizing cyclic spectra to identify periodic-stationary line spectrum characteristics in ship radiated noise. Through classical and modern digital signal processing techniques, this research leverages the cyclic spectrum, frequency-domain coherence in cyclic spectra, and distribution patterns of cyclo frequencies within the cyclic spectrum to propose a novel feature extraction method: the local feature-cyclo-coherence-based approach. This method effectively extracts periodic-stationary features from ship radiated noise and enhances the signal-to-noise ratio (SNR) of cyclic line spectra in weak signals' cyclic spectra. Through simulations and experimental data verification, the proposed feature extraction algorithm demonstrates superior effectiveness compared to traditional methods for extracting features from weak targets and weak frequency components. The methodology presented in this paper provides a valuable technical tool for ship target recognition.
2026,48(3): 127-132 收稿日期：2025-5-29
DOI：10.3404/j.issn.1672-7649.2026.03.020
分类号：U661.44；TB532
作者简介：戴卫国(1968-),男,博士,教授,研究方向为声呐信号处理、水声目标识别
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