{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:38:23Z","timestamp":1760233103609,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T00:00:00Z","timestamp":1670889600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62201007, U21A20457, 62071003","2020M681992","KJ2020A0026","GXXT-2021-028"],"award-info":[{"award-number":["62201007, U21A20457, 62071003","2020M681992","KJ2020A0026","GXXT-2021-028"]}]},{"name":"China Postdoctoral Science Foundation","award":["62201007, U21A20457, 62071003","2020M681992","KJ2020A0026","GXXT-2021-028"],"award-info":[{"award-number":["62201007, U21A20457, 62071003","2020M681992","KJ2020A0026","GXXT-2021-028"]}]},{"name":"Foundation of An\u2019Hui Educational Committee","award":["62201007, U21A20457, 62071003","2020M681992","KJ2020A0026","GXXT-2021-028"],"award-info":[{"award-number":["62201007, U21A20457, 62071003","2020M681992","KJ2020A0026","GXXT-2021-028"]}]},{"name":"Anhui Province University Collaborative Innovation Project","award":["62201007, U21A20457, 62071003","2020M681992","KJ2020A0026","GXXT-2021-028"],"award-info":[{"award-number":["62201007, U21A20457, 62071003","2020M681992","KJ2020A0026","GXXT-2021-028"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The ability to sculpt complex reference waves and probe diverse radiation field patterns have facilitated the rise of metasurface antennas, while there is still a compromise between the required wide operation band and the non-overlapping characteristic of radiation field patterns. Specifically, the current computational image formation process with a classic matched filter and other sparsity-driven algorithms would inevitably face the challenge of a relatively confined scene information sampling ratio and high computational complexity. In this paper, we marry the concepts of a deep convolutional neural network with computational imaging literature. Compared with the current matched filter and compressed sensing reconstruction technique, our proposal could handle a relatively high correlation of measurement modes and low scene sampling ratio. With the delicately trained reconstruction network, point-size objects and more complicated targets can both be quickly and accurately reconstructed. In addition, the unavoidable heavy computation burden and essential large operation frequency band can be effectively mitigated. The simulated experiments with measured radiation field data verify the effectiveness of the proposed method.<\/jats:p>","DOI":"10.3390\/s22249771","type":"journal-article","created":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T04:32:48Z","timestamp":1670905968000},"page":"9771","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Fast Near-Field Frequency-Diverse Computational Imaging Based on End-to-End Deep-Learning Network"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5802-8511","authenticated-orcid":false,"given":"Zhenhua","family":"Wu","sequence":"first","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China"},{"name":"State Key Laboratory of Millimeter Waves, Southeast University, Nanjing 210096, China"},{"name":"East China Research Institute of Electronic Engineering, Hefei 230031, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3820-4119","authenticated-orcid":false,"given":"Fafa","family":"Zhao","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China"}]},{"given":"Man","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9883-7508","authenticated-orcid":false,"given":"Sha","family":"Huan","sequence":"additional","affiliation":[{"name":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China"}]},{"given":"Xueli","family":"Pan","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China"}]},{"given":"Wei","family":"Chen","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China"}]},{"given":"Lixia","family":"Yang","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1860","DOI":"10.1109\/TAP.2020.2968795","article-title":"Review of Metasurface Antennas for Computational Microwave Imaging","volume":"68","author":"Imani","year":"2020","journal-title":"IEEE Trans. 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