Synchrosqueezing-based Short-time Fractional Fourier Transform
A novel synchrosqueezing transform to the time-frequency representation based on short-time fractional Fourier transform for strong time-varying signals is proposed in this paper. To finely describe the local characteristics of nonstationary signal in the short-time fractional Fourier transform doma...
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| Veröffentlicht in: | IEEE transactions on signal processing 2023-01, Vol.71, p.1-15 |
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| creator | Zhao, Zhichun Li, Gang |
| description | A novel synchrosqueezing transform to the time-frequency representation based on short-time fractional Fourier transform for strong time-varying signals is proposed in this paper. To finely describe the local characteristics of nonstationary signal in the short-time fractional Fourier transform domain, a new instantaneous frequency estimator, a new instantaneous fractional frequency estimator and the corresponding energy reassignment operators are given by time-fractional frequency basis. The discrete implementation and signal reconstruction of the proposed method are investigated. Furthermore, the calculation of the optimal fractional order, computational complexity and limitation of the proposed method are discussed. Various strong time-varying signal experiments and time-frequency spectrum energy attenuation gradient extraction experiments of real synthetic aperture radar (SAR) images are conducted to verify the effectiveness and superiority of the proposed method over some advanced time-frequency analysis methods in energy concentration, time-frequency localization, signal reconstruction and clutter suppression. |
| doi_str_mv | 10.1109/TSP.2023.3244097 |
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To finely describe the local characteristics of nonstationary signal in the short-time fractional Fourier transform domain, a new instantaneous frequency estimator, a new instantaneous fractional frequency estimator and the corresponding energy reassignment operators are given by time-fractional frequency basis. The discrete implementation and signal reconstruction of the proposed method are investigated. Furthermore, the calculation of the optimal fractional order, computational complexity and limitation of the proposed method are discussed. Various strong time-varying signal experiments and time-frequency spectrum energy attenuation gradient extraction experiments of real synthetic aperture radar (SAR) images are conducted to verify the effectiveness and superiority of the proposed method over some advanced time-frequency analysis methods in energy concentration, time-frequency localization, signal reconstruction and clutter suppression.</description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/TSP.2023.3244097</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Clutter ; Fourier transforms ; Frequency estimation ; Frequency modulation ; Frequency spectrum ; Phase modulation ; Radar imaging ; short-time fractional Fourier transform ; Signal reconstruction ; Signal resolution ; strong time-varying nonstationary signal ; synchrosqueezing transform ; Synthetic aperture radar ; Time-frequency analysis</subject><ispartof>IEEE transactions on signal processing, 2023-01, Vol.71, p.1-15</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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To finely describe the local characteristics of nonstationary signal in the short-time fractional Fourier transform domain, a new instantaneous frequency estimator, a new instantaneous fractional frequency estimator and the corresponding energy reassignment operators are given by time-fractional frequency basis. The discrete implementation and signal reconstruction of the proposed method are investigated. Furthermore, the calculation of the optimal fractional order, computational complexity and limitation of the proposed method are discussed. Various strong time-varying signal experiments and time-frequency spectrum energy attenuation gradient extraction experiments of real synthetic aperture radar (SAR) images are conducted to verify the effectiveness and superiority of the proposed method over some advanced time-frequency analysis methods in energy concentration, time-frequency localization, signal reconstruction and clutter suppression.</description><subject>Clutter</subject><subject>Fourier transforms</subject><subject>Frequency estimation</subject><subject>Frequency modulation</subject><subject>Frequency spectrum</subject><subject>Phase modulation</subject><subject>Radar imaging</subject><subject>short-time fractional Fourier transform</subject><subject>Signal reconstruction</subject><subject>Signal resolution</subject><subject>strong time-varying nonstationary signal</subject><subject>synchrosqueezing transform</subject><subject>Synthetic aperture radar</subject><subject>Time-frequency analysis</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkD1LA0EQhhdRMEZ7C4sD642zH7cfjSDBqBBQSAS7ZW8zZy4kd3H3UsRf74aksJop3nd45iHklsGIMbAP89nHiAMXI8GlBKvPyIBZyShIrc7zDqWgpdFfl-QqpRUAk9KqAXmc7duwjF362SH-Nu03rXzCRTFbdrGnfbPBYhJ96Juu9eti0u1ig7GYR9-muouba3JR-3XCm9Mcks_J83z8SqfvL2_jpykNnPOehmAWlVK2qk1VgRWqRqGl4KVhvraMcxCSaVb5sgwSNUoTFC5CFbgKQbFSDMn98e42dpk09W6VUTJSclwbsMaCNDkFx1TID6WItdvGZuPj3jFwB0suW3IHS-5kKVfujpUGEf_FQTIrpPgDQ4tjfw</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Zhao, Zhichun</creator><creator>Li, Gang</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>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-9755-2781</orcidid><orcidid>https://orcid.org/0000-0002-6324-944X</orcidid></search><sort><creationdate>20230101</creationdate><title>Synchrosqueezing-based Short-time Fractional Fourier Transform</title><author>Zhao, Zhichun ; Li, Gang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c222t-cc8db669bf8bb0936fe37432581af9122034171ba55c4e7e48c6edcbc26cc6153</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Clutter</topic><topic>Fourier transforms</topic><topic>Frequency estimation</topic><topic>Frequency modulation</topic><topic>Frequency spectrum</topic><topic>Phase modulation</topic><topic>Radar imaging</topic><topic>short-time fractional Fourier transform</topic><topic>Signal reconstruction</topic><topic>Signal resolution</topic><topic>strong time-varying nonstationary signal</topic><topic>synchrosqueezing transform</topic><topic>Synthetic aperture radar</topic><topic>Time-frequency analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhao, Zhichun</creatorcontrib><creatorcontrib>Li, Gang</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Xplore (Online service)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhao, Zhichun</au><au>Li, Gang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Synchrosqueezing-based Short-time Fractional Fourier Transform</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>2023-01-01</date><risdate>2023</risdate><volume>71</volume><spage>1</spage><epage>15</epage><pages>1-15</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract>A novel synchrosqueezing transform to the time-frequency representation based on short-time fractional Fourier transform for strong time-varying signals is proposed in this paper. To finely describe the local characteristics of nonstationary signal in the short-time fractional Fourier transform domain, a new instantaneous frequency estimator, a new instantaneous fractional frequency estimator and the corresponding energy reassignment operators are given by time-fractional frequency basis. The discrete implementation and signal reconstruction of the proposed method are investigated. Furthermore, the calculation of the optimal fractional order, computational complexity and limitation of the proposed method are discussed. Various strong time-varying signal experiments and time-frequency spectrum energy attenuation gradient extraction experiments of real synthetic aperture radar (SAR) images are conducted to verify the effectiveness and superiority of the proposed method over some advanced time-frequency analysis methods in energy concentration, time-frequency localization, signal reconstruction and clutter suppression.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TSP.2023.3244097</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-9755-2781</orcidid><orcidid>https://orcid.org/0000-0002-6324-944X</orcidid></addata></record> |
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| subjects | Clutter Fourier transforms Frequency estimation Frequency modulation Frequency spectrum Phase modulation Radar imaging short-time fractional Fourier transform Signal reconstruction Signal resolution strong time-varying nonstationary signal synchrosqueezing transform Synthetic aperture radar Time-frequency analysis |
| title | Synchrosqueezing-based Short-time Fractional Fourier Transform |
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