基于自适应傅里叶分解的船舶轴频电磁场信号提取

徐震寰; 吴永飞; 裴建新

doi:10.11993/j.issn.2096-3920.2023-0049

基于自适应傅里叶分解的船舶轴频电磁场信号提取

doi: 10.11993/j.issn.2096-3920.2023-0049

1.
太原理工大学计算机科学与技术学院(大数据学院), 山西太原, 030024
2.
中国海洋大学海洋地球科学学院, 山东青岛, 266100
3.
中国海洋大学海底科学与探测技术教育部重点实验室, 山东青岛, 266100

基金项目: 山西省基础研究计划(自由探索类青年科学研究项目)项目资助(202103021223050)

详细信息

作者简介:
徐震寰(1989-), 男, 博士, 讲师, 主要研究方向为海洋电磁信号处理

中图分类号: U674.7; TJ630.34
计量
- 文章访问数: 76
- HTML全文浏览量: 27
- PDF下载量: 34
- 被引次数: 0
出版历程
- 收稿日期: 2023-05-15
- 修回日期: 2023-06-16
- 录用日期: 2023-07-13
- 网络出版日期: 2023-07-25

Extraction of Shaft-Rate Electromagnetic Field of Ships Based on Adaptive Fourier Decomposition

1.
College of Computer Science and Technology(College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China
2.
College of Marine Geosciences, Ocean University of China, Qingdao 266100, China
3.
Key Laboratory of Submarine Geosciences and Prospecting Techniques of Ministry of Education, Ocean University of China, Qingdao 266100, China

摘要

摘要: 船舶轴频电磁场是水面船舶及水下航行器非常关键的特征, 然而由于静态电磁场的存在, 大大降低了轴频电磁场的信噪比。为实现低信噪比情况下微弱轴频电磁场信号的有效检测, 文中提出一种基于自适应傅里叶分解的信号提取方法, 可以将复杂非平稳信号自低频到高频自适应地分解为一系列具有瞬时频率的单分量之和的形式。通过分别处理仿真和实测数据, 结果表明, 该算法能够克服短时傅里叶变换、小波变换及经验模态分解等方法的缺点, 可快速有效地提取到轴频电磁场信号, 进而为后续船舶及水下航行器的定位追踪提供参考。
- 船舶 /
- 轴频电磁场 /
- 自适应傅里叶分解 /
- 信号提取
Abstract: The shaft-rate electromagnetic field is a crucial feature of ships and undersea vehicles. However, due to the presence of static electromagnetic fields, the signal-to-noise ratio of the shaft-rate electromagnetic fields is greatly reduced. To effectively detect weak shaft-rate electromagnetic field signals under low signal-to-noise ratio conditions, this paper proposed a signal extraction method based on adaptive Fourier decomposition(AFD). It could adaptively decompose complex non-stationary signals from low frequency to high frequency into a series of single components with instantaneous frequency. Through simulation and measured data processing, the results show that this algorithm can overcome the shortcomings of methods such as short-time Fourier transform, wavelet transform, and empirical mode decomposition. It can quickly and effectively extract shaft-rate electromagnetic field signals, thereby providing a reference for positioning and tracking other ships and undersea vehicles.
- ship /
- shift-rate electromagnetic field /
- adaptive Fourier decomposition /
- signal extraction

HTML全文

图 1 AFD信号分解过程

Figure 1. Signal decomposition by AFD

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图 2 仿真信号波形及AFD重构结果

Figure 2. Simulation signal waveform and AFD reconstruction results

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图 3 基于AFD提取实测轴频电场信号流程图

Figure 3. Flow chart of extracting measured shaft-rate electric field signals based on AFD

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图 4 实测轴频电磁场提取前后时频图

Figure 4. Time-frequency spectra before and after extracting shaft-rate electromagnetic field

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图 5 基于EMD提取的轴频电磁场及其Hilbert谱

Figure 5. Shaft-rate electromagnetic field and its Hilbert spectrum extracted based on EMD

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