[1]李启飞,吴芳,韩蕾蕾,等.磁异常信号奇异值分解的随机共振检测方法[J].探测与控制学报,2020,42(02):24.[doi:.]
 LI Qifei,WU Fang,HAN Leilei,et al.Stochastic Resonance Detection Method for Magnetic Anomaly Signals Singular Value Decomposition[J].,2020,42(02):24.[doi:.]
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磁异常信号奇异值分解的随机共振检测方法()
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《探测与控制学报》[ISSN:1008-1194/CN:61-1316/TJ]

卷:
42
期数:
2020年02
页码:
24
栏目:
出版日期:
2020-04-15

文章信息/Info

Title:
Stochastic Resonance Detection Method for Magnetic Anomaly Signals Singular Value Decomposition
文章编号:
1008-1194(2020)02-002
作者:
李启飞12吴芳1韩蕾蕾1范赵鹏3李沛宗1
1.海军航空大学,山东 烟台 264001;2.解放军91550部队,辽宁 大连 116000;3.解放军91001部队,北京 100000
Author(s):
LI Qifei12 WU Fang1 HAN Leilei1 FAN Zhaopeng3 LI Peizong1
1. Naval Aeronautics University, Yantai 254001, China; 2. Unit 91550 of PLA, Dalian 116000, China; 3. Unit 91001 of PLA, Beijing 100000, China
关键词:
水下目标 磁偶极子 奇异值分解 随机共振 磁异常信号检测
Keywords:
To solve the problem of detecting the underwater target magnetic anomaly signal from the strong geomagnetic field noise a singular value decomposition-single resonance (SVD-RS) method was proposed. Firstly the input signal was established under different noise intensity by the magnetic dipole model and the most sub signal was chosen by SVD method. SVD method had ideal de-correlation characteristics and could extract useful signals and characteristic information under strong noise. The results showed that this method could improve the signal to noise ratio by about 6 dB. Then the sub-signal was passed through the stochastic resonance system when the test statistic was constructed to detect the magnetic abnormal signal of the underwater target. The results showed that the SVD-RS detection method could effectively detect the magnetic anomaly of underwater targets.
分类号:
TN911.72;TM153.1
DOI:
.
文献标志码:
A
摘要:
针对目前对水下目标磁异常信号低信噪比检测能力较差的问题,提出奇异值分解随机共振(SVD-RS)方法。该方法基于磁偶极子仿真水下目标磁偶极子信号,信号经过奇异值分解选择最优子信号,随后将子信号通过随机共振系统,并构建检验统计量,实现对水下目标磁异常信号的检测。仿真结果表明,通过奇异值分解的方法,能够将信号信噪比提高6 dB,使用奇异值分解随机共振检测方法,能够在输入信噪比为-12 dB时,对水下目标磁异常信号进行有效检测。
Abstract:
underwater target; magnetic dipole; singular value decomposition; stochastic resonance; magnetic anomaly signal detection

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-11-04
基金项目:国家自然科学基金项目资助(61971424)
作者简介:李启飞(1994—),男,江苏扬州人,硕士研究生,研究方向:弱信号检测,磁异常探测。E-mail:lqf_com@163.com
更新日期/Last Update: 2020-05-15