{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:26:33Z","timestamp":1760145993615,"version":"build-2065373602"},"reference-count":56,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T00:00:00Z","timestamp":1726704000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Program of National Natural Science Foundation of China","award":["62331020","62301389"],"award-info":[{"award-number":["62331020","62301389"]}]},{"name":"National Natural Science Foundation of China","award":["62331020","62301389"],"award-info":[{"award-number":["62331020","62301389"]}]},{"name":"Open Fund of the Laboratory of Pinghu","award":["62331020","62301389"],"award-info":[{"award-number":["62331020","62301389"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This manuscript presents a novel framework for high-resolution and robust microwave correlation imaging. In order to generate a more diverse random radiation field distribution, the unified random radiation field (URRF) model is proposed. The URRF model can accurately characterize the joint random modulation in the signals\u2019 phase, amplitude, and frequency. Furthermore, we build a parametric imaging model based on URRF which clearly describes the relationship between the image to be reconstructed and the signals by the URRF model. By using this imaging model, the reconstruction of an image is converted into solving a multi-parameter optimization problem with multiple constraints. To solve this optimization problem with high efficiency and accuracy, the model-constrained adaptive alternating multiple parameter estimation (MC-AAMPE) algorithm is proposed. This algorithm decomposes the high-dimensional multi-parameter optimization problem into several sub-optimization problems. The renewing solutions to these sub-optimization problems make the multi-parameter optimization converge to the image of the target and the parameters of clutter and noise, which are all unknown before the solution. In comparison with the existing methods, the proposed scheme generates images with higher resolution and is more robust under noise conditions. Extensive simulation experiments confirmed the effectiveness and robustness of the proposed method.<\/jats:p>","DOI":"10.3390\/rs16183481","type":"journal-article","created":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T08:12:27Z","timestamp":1726733547000},"page":"3481","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A High-Resolution and Robust Microwave Correlation Imaging Method Based on URRF Using MC-AAMPE Algorithm"],"prefix":"10.3390","volume":"16","author":[{"given":"Min","family":"Xue","sequence":"first","affiliation":[{"name":"The National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Mengdao","family":"Xing","sequence":"additional","affiliation":[{"name":"The National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"},{"name":"The Academy of Advanced Interdisciplinary Research, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Yuexin","family":"Gao","sequence":"additional","affiliation":[{"name":"The School of Aerospace Science and Technology, Xidian University, Xi\u2019an 710071, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-4303-2153","authenticated-orcid":false,"given":"Zhixin","family":"Wu","sequence":"additional","affiliation":[{"name":"The National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0473-1874","authenticated-orcid":false,"given":"Wangshuo","family":"Tang","sequence":"additional","affiliation":[{"name":"The National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Yidi","family":"Wang","sequence":"additional","affiliation":[{"name":"The National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"093602","DOI":"10.1103\/PhysRevLett.93.093602","article-title":"Ghost imaging with thermal light: Comparing entanglement and classical correlation","volume":"93","author":"Gatti","year":"2004","journal-title":"Phys. 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