{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:17:12Z","timestamp":1760149032496,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T00:00:00Z","timestamp":1687737600000},"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","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"],"award-info":[{"award-number":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"]}]},{"name":"State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE) foundation","award":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"],"award-info":[{"award-number":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"]}]},{"name":"Foundation of An\u2019Hui Educational Committee","award":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"],"award-info":[{"award-number":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"]}]},{"name":"Anhui Province University Collaborative Innovation Project","award":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"],"award-info":[{"award-number":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"]}]},{"name":"Shenzhen Science and Technology Program","award":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"],"award-info":[{"award-number":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"]}]},{"name":"Introduced Innovative Research and Development Team Project of The Pearl River Talent Recruitment Program","award":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"],"award-info":[{"award-number":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"]}]},{"name":"China Postdoctoral Science Foundation","award":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"],"award-info":[{"award-number":["62201007","U21A20457","62071003","CEMEE2022Z0302B","KJ2020A0026","GXXT-2021-028","KQTD20190929172704911","2019ZT08X751","2020M681992"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Frequency-diverse radar imaging is an emerging field that combines computational imaging with frequency-diverse techniques to interrogate the high-quality images of objects. Despite the success of deep reconstruction networks in improving scene image reconstruction from noisy or under-sampled frequency-diverse measurements, their reliance on large amounts of high-quality training data and the inherent uninterpretable features pose significant challenges in the design and optimization of imaging networks, particularly in the face of dynamic variations in radar operating frequency bands. Here, aiming at reducing the latency and processing burden involved in scene image reconstruction, we propose an adaptive sampling iterative soft-thresholding deep unfolding network (ASISTA-Net). Specifically, we embed an adaptively sampling module into the iterative soft-thresholding (ISTA) unfolding network, which contains multiple measurement matrices with different compressed sampling ratios. The outputs of the convolutional layers are then passed through a series of ISTA layers that perform a sparse coding step followed by a thresholding step. The proposed method requires no need for heavy matrix operations and massive amount of training scene targets and measurements datasets. Unlike recent work using matrix-inversion-based and data-driven deep reconstruction networks, our generic approach is directly adapted to multi-compressed sampling ratios and multi-scene target image reconstruction, and no restrictions on the types of imageable scenes are imposed. Multiple measurement matrices with different scene compressed sampling ratios are trained in parallel, which enables the frequency-diverse radar to select operation frequency bands flexibly. In general, the application of the proposed approach paves the way for the widespread deployment of computational microwave and millimeter wave frequency-diverse radar imagers to achieve real-time imaging. Extensive imaging simulations demonstrate the effectiveness of our proposed method.<\/jats:p>","DOI":"10.3390\/rs15133284","type":"journal-article","created":{"date-parts":[[2023,6,27]],"date-time":"2023-06-27T01:49:21Z","timestamp":1687830561000},"page":"3284","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Fast Frequency-Diverse Radar Imaging Based on Adaptive Sampling Iterative Soft-Thresholding Deep Unfolding Network"],"prefix":"10.3390","volume":"15","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 Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang 471000, China"},{"name":"State Key Laboratory of Millimeter Waves, Southeast University, Nanjing 210096, 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":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electronics and Communication, Sun Yat-Sen University, Guangzhou 510275, China"}]},{"given":"Yice","family":"Cao","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5823-3144","authenticated-orcid":false,"given":"Jun","family":"Qian","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China"}]},{"given":"Jiafei","family":"Xu","sequence":"additional","affiliation":[{"name":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7943-9846","authenticated-orcid":false,"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":[[2023,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"063019","DOI":"10.1117\/1.JEI.27.6.063019","article-title":"Microwave computational imaging in frequency domain with reprogrammable metasurface","volume":"27","author":"Luo","year":"2018","journal-title":"J. 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