MIMO Radar Codes/Filter Bank Optimization Design in Clutter Environment
Multiple-input multiple-output (MIMO) radar optimization design for extended targets in clutter is a challenging problem owing to the lack of perfect knowledge of the target impulse response (TIR). Assuming uncertain TIR, this article focuses on the joint robust design of the radar codes and filter...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on instrumentation and measurement 2022, Vol.71, p.1-15 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 15 |
|---|---|
| container_issue | |
| container_start_page | 1 |
| container_title | IEEE transactions on instrumentation and measurement |
| container_volume | 71 |
| creator | Yao, Yu Li, Zeqing Liu, Haitao Miao, Pu Wu, Lenan |
| description | Multiple-input multiple-output (MIMO) radar optimization design for extended targets in clutter is a challenging problem owing to the lack of perfect knowledge of the target impulse response (TIR). Assuming uncertain TIR, this article focuses on the joint robust design of the radar codes and filter bank in MIMO structure to improve extended target detection capability in signal-dependent interference environment. Considering the average and the worst case signal-to-interference-plus-noise ratio (SINR) at the output as the performance metrics to maximize, we propose two iterative optimization procedures, under similarity and energy requirements on the radar code. The convergence property and asymptotic optimality of two algorithms are analyzed. Finally, simulation results have displayed that two proposed optimization strategies achieve higher objective values than the existing approaches, and share reasonable computational burden. |
| doi_str_mv | 10.1109/TIM.2022.3184366 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_journals_2682921612</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9800918</ieee_id><sourcerecordid>2682921612</sourcerecordid><originalsourceid>FETCH-LOGICAL-c291t-dbf256511b5360fd92f1307d1e3693ac52e0aee93a16f173e75ae8b9440797e73</originalsourceid><addsrcrecordid>eNo9kEFLAzEQhYMoWKt3wcuC521nkk2yOera1kJLQeo5pN1ZSW13a7IV9Ne7pcXTvMP33sDH2D3CABHMcDmdDzhwPhCYZ0KpC9ZDKXVqlOKXrAeAeWoyqa7ZTYwbANAq0z02mU_ni-TNlS4kRVNSHI79tqWQPLv6M1nsW7_zv671TZ28UPQfdeLrpNge2iMzqr99aOod1e0tu6rcNtLd-fbZ-3i0LF7T2WIyLZ5m6ZobbNNyVXGpJOJKCgVVaXiFAnSJJJQRbi05gSPqIqoKtSAtHeUrk2WgjSYt-uzxtLsPzdeBYms3zSHU3UvLVc4NR4W8o-BErUMTY6DK7oPfufBjEexRl-102aMue9bVVR5OFU9E_7jJAQzm4g_vqmRz</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2682921612</pqid></control><display><type>article</type><title>MIMO Radar Codes/Filter Bank Optimization Design in Clutter Environment</title><source>IEEE Electronic Library (IEL)</source><creator>Yao, Yu ; Li, Zeqing ; Liu, Haitao ; Miao, Pu ; Wu, Lenan</creator><creatorcontrib>Yao, Yu ; Li, Zeqing ; Liu, Haitao ; Miao, Pu ; Wu, Lenan</creatorcontrib><description>Multiple-input multiple-output (MIMO) radar optimization design for extended targets in clutter is a challenging problem owing to the lack of perfect knowledge of the target impulse response (TIR). Assuming uncertain TIR, this article focuses on the joint robust design of the radar codes and filter bank in MIMO structure to improve extended target detection capability in signal-dependent interference environment. Considering the average and the worst case signal-to-interference-plus-noise ratio (SINR) at the output as the performance metrics to maximize, we propose two iterative optimization procedures, under similarity and energy requirements on the radar code. The convergence property and asymptotic optimality of two algorithms are analyzed. Finally, simulation results have displayed that two proposed optimization strategies achieve higher objective values than the existing approaches, and share reasonable computational burden.</description><identifier>ISSN: 0018-9456</identifier><identifier>EISSN: 1557-9662</identifier><identifier>DOI: 10.1109/TIM.2022.3184366</identifier><identifier>CODEN: IEIMAO</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Asymptotic properties ; Azimuth ; Clutter ; Design optimization ; Energy requirements ; Extended target ; filter bank design ; Filter banks ; generalized fractional programming (GFP) ; Impulse response ; Interference ; Iterative methods ; MIMO communication ; minorization-maximization (MM) ; multiple-input multiple-output (MIMO) radar ; Performance measurement ; Radar ; Robust design ; Target detection ; transceiver optimization</subject><ispartof>IEEE transactions on instrumentation and measurement, 2022, Vol.71, p.1-15</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-dbf256511b5360fd92f1307d1e3693ac52e0aee93a16f173e75ae8b9440797e73</citedby><cites>FETCH-LOGICAL-c291t-dbf256511b5360fd92f1307d1e3693ac52e0aee93a16f173e75ae8b9440797e73</cites><orcidid>0000-0001-7514-4701 ; 0000-0002-3052-8709 ; 0000-0003-4096-4501 ; 0000-0002-7282-491X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9800918$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,4009,27902,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9800918$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yao, Yu</creatorcontrib><creatorcontrib>Li, Zeqing</creatorcontrib><creatorcontrib>Liu, Haitao</creatorcontrib><creatorcontrib>Miao, Pu</creatorcontrib><creatorcontrib>Wu, Lenan</creatorcontrib><title>MIMO Radar Codes/Filter Bank Optimization Design in Clutter Environment</title><title>IEEE transactions on instrumentation and measurement</title><addtitle>TIM</addtitle><description>Multiple-input multiple-output (MIMO) radar optimization design for extended targets in clutter is a challenging problem owing to the lack of perfect knowledge of the target impulse response (TIR). Assuming uncertain TIR, this article focuses on the joint robust design of the radar codes and filter bank in MIMO structure to improve extended target detection capability in signal-dependent interference environment. Considering the average and the worst case signal-to-interference-plus-noise ratio (SINR) at the output as the performance metrics to maximize, we propose two iterative optimization procedures, under similarity and energy requirements on the radar code. The convergence property and asymptotic optimality of two algorithms are analyzed. Finally, simulation results have displayed that two proposed optimization strategies achieve higher objective values than the existing approaches, and share reasonable computational burden.</description><subject>Algorithms</subject><subject>Asymptotic properties</subject><subject>Azimuth</subject><subject>Clutter</subject><subject>Design optimization</subject><subject>Energy requirements</subject><subject>Extended target</subject><subject>filter bank design</subject><subject>Filter banks</subject><subject>generalized fractional programming (GFP)</subject><subject>Impulse response</subject><subject>Interference</subject><subject>Iterative methods</subject><subject>MIMO communication</subject><subject>minorization-maximization (MM)</subject><subject>multiple-input multiple-output (MIMO) radar</subject><subject>Performance measurement</subject><subject>Radar</subject><subject>Robust design</subject><subject>Target detection</subject><subject>transceiver optimization</subject><issn>0018-9456</issn><issn>1557-9662</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEFLAzEQhYMoWKt3wcuC521nkk2yOera1kJLQeo5pN1ZSW13a7IV9Ne7pcXTvMP33sDH2D3CABHMcDmdDzhwPhCYZ0KpC9ZDKXVqlOKXrAeAeWoyqa7ZTYwbANAq0z02mU_ni-TNlS4kRVNSHI79tqWQPLv6M1nsW7_zv671TZ28UPQfdeLrpNge2iMzqr99aOod1e0tu6rcNtLd-fbZ-3i0LF7T2WIyLZ5m6ZobbNNyVXGpJOJKCgVVaXiFAnSJJJQRbi05gSPqIqoKtSAtHeUrk2WgjSYt-uzxtLsPzdeBYms3zSHU3UvLVc4NR4W8o-BErUMTY6DK7oPfufBjEexRl-102aMue9bVVR5OFU9E_7jJAQzm4g_vqmRz</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Yao, Yu</creator><creator>Li, Zeqing</creator><creator>Liu, Haitao</creator><creator>Miao, Pu</creator><creator>Wu, Lenan</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0001-7514-4701</orcidid><orcidid>https://orcid.org/0000-0002-3052-8709</orcidid><orcidid>https://orcid.org/0000-0003-4096-4501</orcidid><orcidid>https://orcid.org/0000-0002-7282-491X</orcidid></search><sort><creationdate>2022</creationdate><title>MIMO Radar Codes/Filter Bank Optimization Design in Clutter Environment</title><author>Yao, Yu ; Li, Zeqing ; Liu, Haitao ; Miao, Pu ; Wu, Lenan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-dbf256511b5360fd92f1307d1e3693ac52e0aee93a16f173e75ae8b9440797e73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Asymptotic properties</topic><topic>Azimuth</topic><topic>Clutter</topic><topic>Design optimization</topic><topic>Energy requirements</topic><topic>Extended target</topic><topic>filter bank design</topic><topic>Filter banks</topic><topic>generalized fractional programming (GFP)</topic><topic>Impulse response</topic><topic>Interference</topic><topic>Iterative methods</topic><topic>MIMO communication</topic><topic>minorization-maximization (MM)</topic><topic>multiple-input multiple-output (MIMO) radar</topic><topic>Performance measurement</topic><topic>Radar</topic><topic>Robust design</topic><topic>Target detection</topic><topic>transceiver optimization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yao, Yu</creatorcontrib><creatorcontrib>Li, Zeqing</creatorcontrib><creatorcontrib>Liu, Haitao</creatorcontrib><creatorcontrib>Miao, Pu</creatorcontrib><creatorcontrib>Wu, Lenan</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on instrumentation and measurement</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yao, Yu</au><au>Li, Zeqing</au><au>Liu, Haitao</au><au>Miao, Pu</au><au>Wu, Lenan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MIMO Radar Codes/Filter Bank Optimization Design in Clutter Environment</atitle><jtitle>IEEE transactions on instrumentation and measurement</jtitle><stitle>TIM</stitle><date>2022</date><risdate>2022</risdate><volume>71</volume><spage>1</spage><epage>15</epage><pages>1-15</pages><issn>0018-9456</issn><eissn>1557-9662</eissn><coden>IEIMAO</coden><abstract>Multiple-input multiple-output (MIMO) radar optimization design for extended targets in clutter is a challenging problem owing to the lack of perfect knowledge of the target impulse response (TIR). Assuming uncertain TIR, this article focuses on the joint robust design of the radar codes and filter bank in MIMO structure to improve extended target detection capability in signal-dependent interference environment. Considering the average and the worst case signal-to-interference-plus-noise ratio (SINR) at the output as the performance metrics to maximize, we propose two iterative optimization procedures, under similarity and energy requirements on the radar code. The convergence property and asymptotic optimality of two algorithms are analyzed. Finally, simulation results have displayed that two proposed optimization strategies achieve higher objective values than the existing approaches, and share reasonable computational burden.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIM.2022.3184366</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-7514-4701</orcidid><orcidid>https://orcid.org/0000-0002-3052-8709</orcidid><orcidid>https://orcid.org/0000-0003-4096-4501</orcidid><orcidid>https://orcid.org/0000-0002-7282-491X</orcidid></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 0018-9456 |
| ispartof | IEEE transactions on instrumentation and measurement, 2022, Vol.71, p.1-15 |
| issn | 0018-9456 1557-9662 |
| language | eng |
| recordid | cdi_proquest_journals_2682921612 |
| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Asymptotic properties Azimuth Clutter Design optimization Energy requirements Extended target filter bank design Filter banks generalized fractional programming (GFP) Impulse response Interference Iterative methods MIMO communication minorization-maximization (MM) multiple-input multiple-output (MIMO) radar Performance measurement Radar Robust design Target detection transceiver optimization |
| title | MIMO Radar Codes/Filter Bank Optimization Design in Clutter Environment |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T02%3A13%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=MIMO%20Radar%20Codes/Filter%20Bank%20Optimization%20Design%20in%20Clutter%20Environment&rft.jtitle=IEEE%20transactions%20on%20instrumentation%20and%20measurement&rft.au=Yao,%20Yu&rft.date=2022&rft.volume=71&rft.spage=1&rft.epage=15&rft.pages=1-15&rft.issn=0018-9456&rft.eissn=1557-9662&rft.coden=IEIMAO&rft_id=info:doi/10.1109/TIM.2022.3184366&rft_dat=%3Cproquest_RIE%3E2682921612%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2682921612&rft_id=info:pmid/&rft_ieee_id=9800918&rfr_iscdi=true |