基于改进cohen类的船舶辐射噪声线谱精细特征提取方法

IF 1.5 4区 管理学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Zhe Li, Weiguo Dai, Qijun Liu, Yichuan Wang, Shilin Sun
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引用次数: 0

摘要

舰船辐射噪声线谱是被动声呐探测水声目标的重要特征。然而,由于目标强度较弱、传播衰减严重以及海洋环境噪声,被动声呐接收到的信号普遍表现为信噪比低、非平稳性强、多普勒移线谱被淹没。这些挑战降低了传统的Cohen类时频分布(CCTFD)方法在捕获此类信号的精细频谱特征方面的性能。为了克服这些困难,本研究提出了一种改进的cohen类方法,称为模糊函数-瞬时自相关函数联合滤波Wigner-Ville分布(AIJF-WVD)。首先,本研究分析了标准CCTFD的交叉项抑制机制在处理多分量多普勒移位信号时,如何降低时频分布(TFD)的时频分辨率/浓度。与传统的模糊函数(AF)域沿移频维和时延维二维低通滤波交叉项抑制框架不同,AIJF-WVD提出了一种新颖的联合滤波方法,该方法是在保持时滞维不变的情况下,在AF域沿频移维设计一维有限脉冲响应(FIR)滤波器,并在此基础上在瞬时自相关函数(IAF)域沿时间维设计一维低通滤波器。因此,该方法在保持较低的计算复杂度的同时,提高了TFD交叉项抑制性能和频率分辨率。然后,利用平均结构相似度(MSSIM)、归一化rsamnyi熵(NRE)、半功率带宽(HBW)和平均运行时间对各种CCTFD方法的性能进行了定量评价。最后,通过跟踪偏差分析对多普勒频移的全局频谱估计精度进行了评价。与传统的CCTFDs相比,AIJF-WVD在低信噪比背景噪声中表现出优越的鲁棒性和适应性,这一点在处理模拟信号和海试船舶辐射噪声时得到了证明。此外,改进后的方法还被验证可以显著改善被动声纳的交叉项抑制、时频集中和计算效率特性,同时保持频率分辨率和优越的音调轨迹跟踪能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An Improved Cohen-Class Based Extraction Method for Fine Spectral Feature of Line Spectrum From Ship-Radiated Noise

An Improved Cohen-Class Based Extraction Method for Fine Spectral Feature of Line Spectrum From Ship-Radiated Noise

The line spectrum from ship-radiated noise is a critical feature for passive sonar to detect underwater acoustic targets. However, due to weak target strength as well as severe propagation attenuation and oceanic ambient noise, the signals received by passive sonars generally manifest low signal-to-noise ratio (SNR), strong nonstationarity and overwhelmed Doppler-shifted line spectrum. These challenges deteriorate the performance of conventional Cohen class time frequency distribution (CCTFD) methods in capturing the fine spectral feature of such signals. To overcome these difficulties, this research proposes an improved Cohen-class method, termed ambiguity function-instantaneous autocorrelation function joint filtering Wigner–Ville distribution (AIJF-WVD). First, this study analyses how standard CCTFD's cross-term suppression mechanism degrades time-frequency resolution/concentration in time-frequency distribution (TFD) when processing multicomponent Doppler-shifted signals. Departing from conventional framework of cross-term suppression via two-dimensional low-pass filtering along both frequency-shift dimension and time-delay dimension in ambiguity function (AF) domain, AIJF-WVD presents a novel joint filtering approach that consists of designing one-dimensional finite impulse response (FIR) filter solely along frequency-shift dimension in AF domain (while maintaining time-delay dimension unchanged) as well as subsequent one-dimensional low-pass filtering along time dimension in instantaneous autocorrelation function (IAF) domain based on the designed filter. Therefore, this novel method enhances TFD performance of cross-term suppression and frequency resolution simultaneously while maintaining low computational complexity. Then, the performances of various CCTFD methods are quantitatively assessed using mean structural similarity (MSSIM), normalised Rényi entropy (NRE), half-power bandwidth (HBW) and mean runtime. Finally, the global spectral estimation accuracy of Doppler-shifted tonals is evaluated through tracking deviation analysis. Compared to conventional CCTFDs, AIJF-WVD exhibits superior robustness and adaptability in low-SNR background noise as evidenced by processing both simulated signals and ship-radiated noise from sea trials. Furthermore, the refined approach is also validated to significantly improve cross-term suppression, time-frequency concentration and computational efficiency characteristics while preserving frequency resolution and superior tonal trajectory tracking capability for passive sonar.

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来源期刊
Iet Radar Sonar and Navigation
Iet Radar Sonar and Navigation 工程技术-电信学
CiteScore
4.10
自引率
11.80%
发文量
137
审稿时长
3.4 months
期刊介绍: IET Radar, Sonar & Navigation covers the theory and practice of systems and signals for radar, sonar, radiolocation, navigation, and surveillance purposes, in aerospace and terrestrial applications. Examples include advances in waveform design, clutter and detection, electronic warfare, adaptive array and superresolution methods, tracking algorithms, synthetic aperture, and target recognition techniques.
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