{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T22:35:03Z","timestamp":1769553303738,"version":"3.49.0"},"reference-count":21,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,4,5]],"date-time":"2024-04-05T00:00:00Z","timestamp":1712275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2021A1515012009"],"award-info":[{"award-number":["2021A1515012009"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Oceanic targets, including ripples, islands, vessels, and coastlines, display distinct sparse characteristics, rendering the ocean a significant arena for sparse Synthetic Aperture Radar (SAR) imaging rooted in sparse signal processing. Deep neural networks (DNNs), a current research emphasis, have, when integrated with sparse SAR, attracted notable attention for their exceptional imaging capabilities and high computational efficiency. Yet, the efficiency of traditional unfolding techniques is impeded by their architecturally inefficient design, which curtails their information transmission capacity and consequently detracts from the quality of reconstruction. This paper unveils a novel Memory-Augmented Deep Unfolding Network (MADUN) for SAR imaging in marine environments. Our methodology harnesses the synergies between deep learning and algorithmic unfolding, enhanced with a memory component, to elevate SAR imaging\u2019s computational precision. At the heart of our investigation is the incorporation of High-Throughput Short-Term Memory (HSM) and Cross-Stage Long-Term Memory (CLM) within the MADUN framework, ensuring robust information flow across unfolding stages and solidifying the foundation for deep, long-term informational correlations. Our experimental results demonstrate that our strategy significantly surpasses existing methods in enhancing the reconstruction of sparse marine scenes.<\/jats:p>","DOI":"10.3390\/rs16071289","type":"journal-article","created":{"date-parts":[[2024,4,8]],"date-time":"2024-04-08T03:11:33Z","timestamp":1712545893000},"page":"1289","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Sparse SAR Imaging Algorithm in Marine Environments Based on Memory-Augmented Deep Unfolding Network"],"prefix":"10.3390","volume":"16","author":[{"given":"Yao","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengwen","family":"Ou","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"He","family":"Tian","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Scattering and Radiation, Beijing 100854, China"},{"name":"Beijing Institute of Environment Features, Beijing 100854, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0633-7224","authenticated-orcid":false,"given":"Bingo Wing-Kuen","family":"Ling","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ye","family":"Tian","sequence":"additional","affiliation":[{"name":"China Telecom Satellite Application Technology Research Institute, Beijing 100035, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3192-3476","authenticated-orcid":false,"given":"Zhe","family":"Zhang","sequence":"additional","affiliation":[{"name":"Suzhou Key Laboratory of Microwave Imaging, Processing and Application Technology, Suzhou 215000, China"},{"name":"Suzhou Aerospace Information Research Institute, Suzhou 215000, China"},{"name":"National Key Laboratory of Microwave Imaging Technology, Beijing 100190, China"},{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wei, X.Y., Zheng, W., Xi, C.P., and Shang, S. 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