Research on Ship Radiated Noise Separation Method Based on Neural Network Autoencoder Combined With Time-Frequency Masking

Strong narrowband signals mixed with weak broadband signals can interfere with the direction estimation of broadband targets using the cross-correlation method of a two-hydrophone array. To tackle this problem, this article proposes a method for separating narrowband signals from sonar-received sign...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IEEE journal of oceanic engineering Ročník 50; číslo 4; s. 3248 - 3263
Hlavní autori:	Xia, Zhi, Zhang, Ziang, Shi, Jie, Zhao, Zihao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.10.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Autoencoders Broadband Broadband communication Correlation Cross correlation Direction-of-arrival (DOA) estimation Direction-of-arrival estimation Frequency distribution Hydrophones Marine vehicles Masking Narrowband Neural networks passive sonar detection Propellers Sonar Sonar detection Spectrogram Time-frequency analysis time-frequency masking Velocity control
ISSN:	0364-9059, 1558-1691
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Abstract	Strong narrowband signals mixed with weak broadband signals can interfere with the direction estimation of broadband targets using the cross-correlation method of a two-hydrophone array. To tackle this problem, this article proposes a method for separating narrowband signals from sonar-received signals. The proposed method integrates neural network autoencoders with time-frequency masking techniques. We have designed a lightweight neural network autoencoder that can be trained using purely simulated data. This autoencoder extracts narrowband line spectrum features from the time-frequency distribution of the sonar-received signals and generates time-frequency masks. Subsequently, the time-frequency masking method is employed to isolate the narrowband components from the sonar-received signals. The proposed method was validated using data from the SWellEx-96 experiment. In the cross-correlation results of the original data from two hydrophones, strong narrowband signals dominated and obscured the weaker broadband signals. By removing the narrowband components from the two-hydrophone signals using the method proposed in this article, the cross-correlation of the processed data clearly revealed the time history of the broadband signal characteristics. This result confirms the effectiveness of the proposed method.
AbstractList	Strong narrowband signals mixed with weak broadband signals can interfere with the direction estimation of broadband targets using the cross-correlation method of a two-hydrophone array. To tackle this problem, this article proposes a method for separating narrowband signals from sonar-received signals. The proposed method integrates neural network autoencoders with time-frequency masking techniques. We have designed a lightweight neural network autoencoder that can be trained using purely simulated data. This autoencoder extracts narrowband line spectrum features from the time-frequency distribution of the sonar-received signals and generates time-frequency masks. Subsequently, the time-frequency masking method is employed to isolate the narrowband components from the sonar-received signals. The proposed method was validated using data from the SWellEx-96 experiment. In the cross-correlation results of the original data from two hydrophones, strong narrowband signals dominated and obscured the weaker broadband signals. By removing the narrowband components from the two-hydrophone signals using the method proposed in this article, the cross-correlation of the processed data clearly revealed the time history of the broadband signal characteristics. This result confirms the effectiveness of the proposed method.
Author	Xia, Zhi Shi, Jie Zhao, Zihao Zhang, Ziang
Author_xml	– sequence: 1 givenname: Zhi surname: Xia fullname: Xia, Zhi email: xz885511@hrbeu.edu.cn organization: National Key Laboratory of Underwater Acoustic Technology, Key Laboratory of Marine Information Acquisition, Security (Harbin Engineering University), Ministry of Industry, Information Technology, College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, China – sequence: 2 givenname: Ziang surname: Zhang fullname: Zhang, Ziang email: zhangziang666@hrbeu.edu.cn organization: National Key Laboratory of Underwater Acoustic Technology, Key Laboratory of Marine Information Acquisition, Security (Harbin Engineering University), Ministry of Industry, Information Technology, College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, China – sequence: 3 givenname: Jie orcidid: 0000-0003-0369-5306 surname: Shi fullname: Shi, Jie email: shijie@hrbeu.edu.cn organization: National Key Laboratory of Underwater Acoustic Technology, Key Laboratory of Marine Information Acquisition, Security (Harbin Engineering University), Ministry of Industry, Information Technology, College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, China – sequence: 4 givenname: Zihao orcidid: 0009-0002-7833-3457 surname: Zhao fullname: Zhao, Zihao organization: National Key Laboratory of Underwater Acoustic Technology, Key Laboratory of Marine Information Acquisition, Security (Harbin Engineering University), Ministry of Industry, Information Technology, College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, China
BookMark	eNpFkM1LAzEQxYMoWKt3Dx4CnrdONslmc6zF-oG2UBWPS7qZtdF2U5MtUv96oxU8DTPvvZnhd0T2W98iIacMBoyBvribXg1yyOWASw2g8j3SY1KWGSs02yc94IXINEh9SI5ifANgQijdI18zjGhCvaC-pY8Lt6YzY53p0NKJdxHpI65NMJ1L8gN2C2_ppYlJTf0EN8EsU-k-fXinw03nsa29xUBHfjV3bbK9uG5Bn9wKs3HAj03St_TBxHfXvh6Tg8YsI5781T55Hl89jW6y--n17Wh4n9W5UF1m0AgAsCpXYi4aKQ2UvFBlA2WJpdUKGzOHEoxsuAXFBVfW2rzWacJKzXifnO_2roNPH8SuevOb0KaTFc-LQhZS_Lpg56qDjzFgU62DW5mwrRhUP4SrRLj6IVz9EU6Rs13EIeK_nbFCcgH8G0NHeS8
CODEN	IJOEDY
Cites_doi	10.1016/j.oceaneng.2022.112626 10.3390/jmse4040070 10.1088/0967-3334/26/1/r02 10.1109/78.726803 10.1109/97.847366 10.1121/10.0011730 10.1109/TCOMM.2006.876855 10.1121/1.428344 10.1121/1.3664100 10.1121/1.2354003 10.1109/JOE.2022.3180764 10.1121/1.4824632 10.1109/JSEN.2017.2676012 10.1016/j.oceaneng.2018.06.036 10.1109/TWC.2013.052213.121090 10.1109/TAES.2024.3417435 10.3390/mca28020042 10.1121/10.0011809 10.1109/TSP.2004.828896 10.1109/TIM.2022.3232095 10.1109/TAES.2003.1207256 10.1121/10.0016837 10.1155/2022/8092706 10.3389/fmars.2022.1097003 10.1121/1.2933858 10.1121/10.0002172 10.1109/TASLP.2019.2915167 10.1121/1.2933865 10.1016/j.apacoust.2006.04.001 10.1121/1.4788165 10.1121/10.0017256 10.1109/TGRS.2011.2164409 10.1007/s11804-016-1352-z 10.3390/rs15030846 10.1121/10.0006389 10.1121/1.4980856 10.1016/j.oceaneng.2024.118188 10.1109/79.587051
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
DBID	97E RIA RIE AAYXX CITATION 7SC 7SP 7TB 7TN 8FD F1W FR3 H96 JQ2 KR7 L.G L7M L~C L~D
DOI	10.1109/JOE.2025.3590072
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Mechanical & Transportation Engineering Abstracts Oceanic Abstracts Technology Research Database ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources ProQuest Computer Science Collection Civil Engineering Abstracts Aquatic Science & Fisheries Abstracts (ASFA) Professional Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional
DatabaseTitle	CrossRef Civil Engineering Abstracts Aquatic Science & Fisheries Abstracts (ASFA) Professional Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Computer and Information Systems Abstracts Professional Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources Oceanic Abstracts ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database Advanced Technologies Database with Aerospace
DatabaseTitleList	Civil Engineering Abstracts
Database_xml	– sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Oceanography
EISSN	1558-1691
EndPage	3263
ExternalDocumentID	10_1109_JOE_2025_3590072 11165340
Genre	orig-research
GrantInformation_xml	– fundername: National Natural Science Foundation of China grantid: 62171148; 52271342; 52171333; 52250344; 52327901 funderid: 10.13039/501100001809
GroupedDBID	-~X .DC 0R~ 29I 4.4 5GY 5VS 66. 6IK 97E AAJGR AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACGFS ACIWK ACNCT AENEX AETIX AGQYO AGSQL AHBIQ AI. AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD HZ~ H~9 IBMZZ ICLAB IFIPE IFJZH IPLJI JAVBF LAI M43 O9- OCL P2P RIA RIE RNS TAE TN5 VH1 ~02 AAYXX CITATION 7SC 7SP 7TB 7TN 8FD F1W FR3 H96 JQ2 KR7 L.G L7M L~C L~D
ID	FETCH-LOGICAL-c247t-aea4000d7274b4f55a083678f088e8d97efab080a5f3d073437ddd2c90a518913
IEDL.DBID	RIE
ISICitedReferencesCount	0
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001575956500001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0364-9059
IngestDate	Thu Oct 30 01:19:44 EDT 2025 Sat Nov 29 06:58:51 EST 2025 Wed Nov 05 07:07:57 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	4
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c247t-aea4000d7274b4f55a083678f088e8d97efab080a5f3d073437ddd2c90a518913
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0003-0369-5306 0009-0002-7833-3457
PQID	3266565491
PQPubID	85484
PageCount	16
ParticipantIDs	ieee_primary_11165340 crossref_primary_10_1109_JOE_2025_3590072 proquest_journals_3266565491
PublicationCentury	2000
PublicationDate	2025-10-01
PublicationDateYYYYMMDD	2025-10-01
PublicationDate_xml	– month: 10 year: 2025 text: 2025-10-01 day: 01
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	IEEE journal of oceanic engineering
PublicationTitleAbbrev	JOE
PublicationYear	2025
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref35 ref12 ref34 ref15 ref37 ref14 ref36 ref31 ref30 ref11 ref33 ref10 ref32 ref2 ref1 ref17 ref16 ref38 ref19 ref18 ref24 ref23 ref26 ref25 ref20 ref22 ref21 ref28 ref27 ref29 ref8 ref7 ref9 ref4 ref3 ref6 ref5 Che (ref39) 2010; 31
References_xml	– ident: ref9 doi: 10.1016/j.oceaneng.2022.112626 – ident: ref36 doi: 10.3390/jmse4040070 – ident: ref25 doi: 10.1088/0967-3334/26/1/r02 – ident: ref27 doi: 10.1109/78.726803 – ident: ref26 doi: 10.1109/97.847366 – ident: ref4 doi: 10.1121/10.0011730 – ident: ref23 doi: 10.1109/TCOMM.2006.876855 – ident: ref32 doi: 10.1121/1.428344 – ident: ref33 doi: 10.1121/1.3664100 – ident: ref14 doi: 10.1121/1.2354003 – ident: ref11 doi: 10.1109/JOE.2022.3180764 – ident: ref30 doi: 10.1121/1.4824632 – volume: 31 start-page: 837 issue: 7 year: 2010 ident: ref39 article-title: Interpreting features of a propellers cavitation spectrum publication-title: J. Harbin Eng. Univ. – ident: ref20 doi: 10.1109/JSEN.2017.2676012 – ident: ref35 doi: 10.1016/j.oceaneng.2018.06.036 – ident: ref21 doi: 10.1109/TWC.2013.052213.121090 – ident: ref12 doi: 10.1109/TAES.2024.3417435 – ident: ref34 doi: 10.3390/mca28020042 – ident: ref28 doi: 10.1121/10.0011809 – ident: ref31 doi: 10.1109/TSP.2004.828896 – ident: ref7 doi: 10.1109/TIM.2022.3232095 – ident: ref37 doi: 10.1109/TAES.2003.1207256 – ident: ref3 doi: 10.1121/10.0016837 – ident: ref10 doi: 10.1155/2022/8092706 – ident: ref16 doi: 10.3389/fmars.2022.1097003 – ident: ref1 doi: 10.1121/1.2933858 – ident: ref38 doi: 10.1121/10.0002172 – ident: ref29 doi: 10.1109/TASLP.2019.2915167 – ident: ref2 doi: 10.1121/1.2933865 – ident: ref13 doi: 10.1016/j.apacoust.2006.04.001 – ident: ref6 doi: 10.1121/1.4788165 – ident: ref8 doi: 10.1121/10.0017256 – ident: ref22 doi: 10.1109/TGRS.2011.2164409 – ident: ref18 doi: 10.1007/s11804-016-1352-z – ident: ref19 doi: 10.3390/rs15030846 – ident: ref5 doi: 10.1121/10.0006389 – ident: ref17 doi: 10.1121/1.4980856 – ident: ref15 doi: 10.1016/j.oceaneng.2024.118188 – ident: ref24 doi: 10.1109/79.587051
SSID	ssj0014479
Score	2.4394138
SecondaryResourceType	review_article
Snippet	Strong narrowband signals mixed with weak broadband signals can interfere with the direction estimation of broadband targets using the cross-correlation method...
SourceID	proquest crossref ieee
SourceType	Aggregation Database Index Database Publisher
StartPage	3248
SubjectTerms	Autoencoders Broadband Broadband communication Correlation Cross correlation Direction-of-arrival (DOA) estimation Direction-of-arrival estimation Frequency distribution Hydrophones Marine vehicles Masking Narrowband Neural networks passive sonar detection Propellers Sonar Sonar detection Spectrogram Time-frequency analysis time-frequency masking Velocity control
Title	Research on Ship Radiated Noise Separation Method Based on Neural Network Autoencoder Combined With Time-Frequency Masking
URI	https://ieeexplore.ieee.org/document/11165340 https://www.proquest.com/docview/3266565491
Volume	50
WOSCitedRecordID	wos001575956500001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1558-1691 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0014479 issn: 0364-9059 databaseCode: RIE dateStart: 19760101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NT4MwFG908aAmfkyN02l68OKBjUKhcJxmizEZM07jbqRrS8YFlsFM9K_3tYAfMR68QSmU9LWvv9f3-nsIXQmZCD9xAbklhFo0CaXF9S3oY9_zJPM5ESbZBIuiYDYLH-rD6uYsjFLKBJ-pnr40vnyZi7XeKusTzRXjUrDQNxnzq8Nany4DSitiPdenVgigofFJ2mH_fjIES9Dxeq7OkcmcH2uQSarySxOb5WW0_88fO0B7NY7Eg0rwh2hDZW20841dsI12J0LxrKakPkLvTZAdzjM8XaRL_Kh5CQBx4ihPC4WnquIBh8djk1ca38ASJ3V1TeEBrUVVzDgerMtcE2BKtcKgUMC4hmovabnA-kSJNVpV8dlveMwLvRV_jJ5Hw6fbO6vOvGAJh7LS4orD3LYlgBs6p4nncU1izYIEdJIKZMhUwueANbmXuBKUBHWZlNIRIZQQ7fg8Qa0sz9Qpwr7wAx8GChSCFU5sTiiAGGiAEHcOUuyg60YW8bIi2IiNYWKHMcgt1nKLa7l10LHu-696dbd3ULeRXlxPwSIGXApYFcxfcvbHa-doW3-9Cs3rola5WqsLtCVey7RYXZrR9QH39s1b
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT8MwDLYQIPGQeA4xGJADFw6FZU2b9TgQE68VxENwq7IkFbu0aOuQ4Ndjpx0PIQ7c-kiVKk6cz7H9GWBfm1SHqY_ILeXCE2lkPEW3qI_DIDAyVFy7YhMyjttPT9FNlazucmGstS74zB7SpfPlm1yP6ajsiBNXjC_QQp-h0llVutan00CIklrPD4UXIWyYeCWb0dHF9Snagq3g0KcqmbL1YxdyZVV-6WK3wXSX__lrK7BUIUnWKUW_ClM2W4OFb_yCa7B4ra3KKlLqdXifhNmxPGN3z4MXdkvMBIg5WZwPRpbd2ZIJHF_3XGVpdoybnKHmROKBvcVl1DjrjIucKDCNHTJUKWheY7PHQfHMKKfE6w7LCO031lMjOoyvwUP39P7kzKtqL3i6JWThKatwdTcNwhvRF2kQKKKxlu0UtZJtm0jaVPURbaog9Q2qCeFLY0xLR_iEk-tzA6azPLObwEIdtkOcKvgQ7XDeVFwgjMEOOPf7UoZ1OJjIInkpKTYSZ5o0owTllpDckkpudajR2H-1q4a9Do2J9JJqEY4SRKaIVtEA5lt_fLYHc2f3vavk6jy-3IZ56qkM1GvAdDEc2x2Y1a_FYDTcdTPtA9Ya0KQ
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Research+on+Ship+Radiated+Noise+Separation+Method+Based+on+Neural+Network+Autoencoder+Combined+With+Time-Frequency+Masking&rft.jtitle=IEEE+journal+of+oceanic+engineering&rft.au=Xia%2C+Zhi&rft.au=Zhang%2C+Ziang&rft.au=Shi%2C+Jie&rft.au=Zhao%2C+Zihao&rft.date=2025-10-01&rft.pub=IEEE&rft.issn=0364-9059&rft.volume=50&rft.issue=4&rft.spage=3248&rft.epage=3263&rft_id=info:doi/10.1109%2FJOE.2025.3590072&rft.externalDocID=11165340
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0364-9059&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0364-9059&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0364-9059&client=summon