基于EEMD和DWT的弱磁异常信号提取方法

宁文茜; 王艳华; 樊黎明; 张晓峻; 谢志臻

doi:10.11993/j.issn.2096-3920.2023-0069

基于EEMD和DWT的弱磁异常信号提取方法

doi: 10.11993/j.issn.2096-3920.2023-0069

宁文茜^{1, 2,},
王艳华^{1, 3,},
樊黎明^{1, 2, 3, ,},
张晓峻^4,,
谢志臻^1,

1.
西北工业大学航海学院, 陕西西安, 710077
2.
自然资源部海洋环境探测技术与应用重点实验室, 广东广州, 510300
3.
西北工业大学青岛研究院, 山东青岛, 266200
4.
哈尔滨工程大学物理与光电学院, 黑龙江哈尔滨, 150001

基金项目: 自然资源部海洋环境探测技术与应用重点实验室开放基金(MESTA-2020-B009); 陕西省自然科学基础研究计划项目(2020JQ-151); 中央高校基本科研业务费项目资助(D5000220158)

详细信息

作者简介:
宁文茜(1998-), 女, 在读硕士, 研究方向为水下弱磁异常探测

通讯作者:
樊黎明(1986-), 男, 博士, 助理教授, 研究方向为水下磁异常探测与目标定位、磁传感器优化设计等

中图分类号: TJ630.34; U674
计量
- 文章访问数: 336
- HTML全文浏览量: 77
- PDF下载量: 82
- 被引次数: 0
出版历程
- 收稿日期: 2023-06-01
- 修回日期: 2023-07-08
- 录用日期: 2023-08-09
- 网络出版日期: 2023-08-14

Weak Magnetic Anomaly Signal Extraction Method Based on EEMD and DWT

NING Wenxi^{1, 2
,},
WANG Yanhua^{1, 3
,},
FAN Liming^{1, 2, 3
, ,},
ZHANG Xiaojun^4
,,
XIE Zhizhen^1
,

1.
School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China
2.
Key Laboratory of Marine Environmental Survey Technology and Application, Ministry of Natural Resources, Guangzhou 510300, China
3.
Qingdao Research Institute, Northwestern Polytechnical University, Qingdao 266200, China
4.
School of Physics and Optoelectronic Engineering, Harbin Engineering University, Harbin 150001, China

摘要

摘要: 磁异常信号中蕴含着丰富的目标特征信息, 是开展目标定位与识别的基础。然而, 目标的磁异常随着探测距离快速衰减, 使得远距离目标的弱磁异常信号通常埋藏在磁噪声中。针对低信噪比下弱磁异常信号的获取问题, 提出基于集合经验模态分解(EEMD)和离散小波变化(DWT)的弱磁异常信号提取方法。首先, 采用EEMD将弱磁异常信号分解为信号域磁信号和噪声域磁信号。随后, 利用DWT的近似系数表征低频信号的特性, 获取噪声域磁信号的低频信号。最后, 将信号域磁信号与噪声域的低频信号进行叠加, 从而获得弱磁异常信号。为了验证该方法的有效性, 开展仿真实验和外场试验。结果表明: 该方法能够有效地抑制背景磁噪声, 提取目标弱磁异常信号, 可为远距离目标的定位与识别提供有效的磁异常数据。
- 弱磁异常 /
- 信号提取 /
- 集合经验模态分解 /
- 离散小波变化 /
- 噪声抑制
Abstract: Magnetic anomaly signal contains rich feature information of targets, which is the basis for target localization and identification. However, the magnetic anomaly generated by the target rapidly attenuates with detection distance, making the weak magnetic anomaly signals of distant targets typically buried in magnetic noise. In view of extracting weak magnetic anomaly signals with a low signal-to-noise ratio, the method of weak magnetic anomaly signal extraction based on ensemble empirical mode decomposition(EEMD) and discrete wavelet transform(DWT) was proposed. Firstly, EEMD was used to decompose the weak magnetic anomaly signal into signal-domain magnetic signal and noise-domain magnetic signal. Then, the approximate coefficient of DWT was used to characterize the characteristics of the low-frequency signal and obtain the low-frequency noise-domain magnetic signal. Finally, the signal-domain magnetic signal was combined with the low-frequency noise-domain magnetic signal to obtain the weak magnetic anomaly signal. In order to validate the effectiveness of this method, simulation experiments and field experiments were carried out. The experimental results show that this method can effectively suppress background magnetic noise and extract weak magnetic anomaly signals of targets. This method can also offer effective data for the localization and identification of distant targets.
- weak magnetic anomaly /
- signal extraction /
- ensemble empirical mode decomposition /
- discrete wavelet transform /
- noise suppression

HTML全文

图 1 基于EEMD-DWT的弱磁异常提取方法框图

Figure 1. Block diagram of weak magnetic anomaly extrac- tion method based on EEDM-DWT

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图 2 一维磁传感器阵列

Figure 2. One-dimensional magnetic sensor array

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图 3 合成的磁异常信号

Figure 3. Synthetic magnetic anomaly signal

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图 4 不同方法的弱磁异常提取结果

Figure 4. Results of weak magnetic anomaly signal extraction using different methods

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图 5 不同方法的RMSE结果

Figure 5. Results of RMSE using different methods

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图 6 河道岸边磁场测量现场

Figure 6. Scene of magnetic field measurement at river bank

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图 7 实测磁异常信号提取

Figure 7. Measured magnetic anomaly signal extraction

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