Piston Sensing for Sparse Aperture Systems via All-Optical Diffractive Neural Network
It is a crucial issue to realize real-time piston correction in the area of sparse aperture imaging. This paper demonstrates that an optical diffractive neural network is capable of achieving light-speed piston sensing. By using detectable intensity distributions to represent pistons, the proposed m...
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| Veröffentlicht in: | IEEE photonics journal 2024-10, Vol.16 (5), p.1-6 |
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| creator | Ma, Xiafei Xie, Zongliang Ma, Haotong Ren, Ge |
| description | It is a crucial issue to realize real-time piston correction in the area of sparse aperture imaging. This paper demonstrates that an optical diffractive neural network is capable of achieving light-speed piston sensing. By using detectable intensity distributions to represent pistons, the proposed method can convert the imaging optical field into estimated pistons without imaging acquisition and electrical processing, thus realizing the piston sensing task all-optically. The simulations verify the feasibility of the approach for fine phasing, with testing accuracy of λ/40 attained. This method can greatly improve the real-time performance of piston sensing and contribute to the development of sparse aperture system. |
| doi_str_mv | 10.1109/JPHOT.2023.3319629 |
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This method can greatly improve the real-time performance of piston sensing and contribute to the development of sparse aperture system.</description><subject>Adaptive optics</subject><subject>Apertures</subject><subject>diffractive neural network</subject><subject>Optical diffraction</subject><subject>Optical imaging</subject><subject>Optical sensors</subject><subject>Piston sensing</subject><subject>Pistons</subject><subject>sparse aperture system</subject><subject>Testing</subject><issn>1943-0655</issn><issn>1943-0647</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNkNtqAjEQhkNpodb2BUov8gJrc9hNNpdiD1pEBfU6ZJNZiV1dSVaLb9_1QOnVDD_83wwfQs-U9Cgl6vVrNpwueoww3uOcKsHUDepQlfKEiFTe_u1Zdo8eYlwTIhTNVActZz429RbPYRv9doXLOuD5zoQIuL-D0OwD4PkxNrCJ-OAN7ldVMt013poKv_myDMY2_gB4AvvQRhNofurw_YjuSlNFeLrOLlp-vC8Gw2Q8_RwN-uPEcqaaxFAKLKVKlYLmjhWUW1IaxqwlEqzIHc9znkujHOUZJ5DlkrtCOJCFzJ3jvItGF66rzVrvgt-YcNS18foc1GGlTWifrUCLsrDUKqeIEu3J1AglmXTCsdQZCrZlsQvLhjrGAOUfjxJ9kqzPkvVJsr5Kbksvl5IHgH8FJjLCGf8Fqq94-A</recordid><startdate>20241001</startdate><enddate>20241001</enddate><creator>Ma, Xiafei</creator><creator>Xie, Zongliang</creator><creator>Ma, Haotong</creator><creator>Ren, Ge</creator><general>IEEE</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-8557-5177</orcidid><orcidid>https://orcid.org/0000-0002-8553-2537</orcidid><orcidid>https://orcid.org/0000-0001-8359-370X</orcidid></search><sort><creationdate>20241001</creationdate><title>Piston Sensing for Sparse Aperture Systems via All-Optical Diffractive Neural Network</title><author>Ma, Xiafei ; Xie, Zongliang ; Ma, Haotong ; Ren, Ge</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c329t-a11e24199f618d2b13c0fa22cc07ec68d388387a9d13530e5873db6de7b78dd33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adaptive optics</topic><topic>Apertures</topic><topic>diffractive neural network</topic><topic>Optical diffraction</topic><topic>Optical imaging</topic><topic>Optical sensors</topic><topic>Piston sensing</topic><topic>Pistons</topic><topic>sparse aperture system</topic><topic>Testing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ma, Xiafei</creatorcontrib><creatorcontrib>Xie, Zongliang</creatorcontrib><creatorcontrib>Ma, Haotong</creatorcontrib><creatorcontrib>Ren, Ge</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE photonics journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ma, Xiafei</au><au>Xie, Zongliang</au><au>Ma, Haotong</au><au>Ren, Ge</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Piston Sensing for Sparse Aperture Systems via All-Optical Diffractive Neural Network</atitle><jtitle>IEEE photonics journal</jtitle><stitle>JPHOT</stitle><date>2024-10-01</date><risdate>2024</risdate><volume>16</volume><issue>5</issue><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>1943-0655</issn><eissn>1943-0647</eissn><coden>PJHOC3</coden><abstract>It is a crucial issue to realize real-time piston correction in the area of sparse aperture imaging. 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| source | IEEE Open Access Journals; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Adaptive optics Apertures diffractive neural network Optical diffraction Optical imaging Optical sensors Piston sensing Pistons sparse aperture system Testing |
| title | Piston Sensing for Sparse Aperture Systems via All-Optical Diffractive Neural Network |
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