{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:42:22Z","timestamp":1760146942305,"version":"build-2065373602"},"reference-count":58,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2024,12,21]],"date-time":"2024-12-21T00:00:00Z","timestamp":1734739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Youth Talent Lifting Project of the China Association for Science and Technology","award":["2021-JCJQ-QT-018","62201611","62301597","62301598","2023-JC-QN-0647","2023-JC-YB-488"],"award-info":[{"award-number":["2021-JCJQ-QT-018","62201611","62301597","62301598","2023-JC-QN-0647","2023-JC-YB-488"]}]},{"name":"National Natural Science Foundation of China","award":["2021-JCJQ-QT-018","62201611","62301597","62301598","2023-JC-QN-0647","2023-JC-YB-488"],"award-info":[{"award-number":["2021-JCJQ-QT-018","62201611","62301597","62301598","2023-JC-QN-0647","2023-JC-YB-488"]}]},{"name":"Natural Science Foundation of Shannxi Province","award":["2021-JCJQ-QT-018","62201611","62301597","62301598","2023-JC-QN-0647","2023-JC-YB-488"],"award-info":[{"award-number":["2021-JCJQ-QT-018","62201611","62301597","62301598","2023-JC-QN-0647","2023-JC-YB-488"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>An intelligent approach is proposed and investigated in this paper for the detection of ultra-low-altitude sea-skimming moving targets for airborne pulse Doppler radar. Without suppressing interferences, the proposed method uses both target and multipath information for detection based on their distinguishable image features and deep learning (DL) techniques. First, the image features of the target, multipath, and sea clutter in the real-measured range-Doppler (RD) map are analyzed, based on which the target and multipath are defined together as the generalized target. Then, based on the composite electromagnetic scattering mechanism of the target and the ocean surface, a scattering-based echo generation model is established and validated to generate sufficient data for DL network training. Finally, the RD features of the generalized target are learned by training the DL-based target detector, such as you-only-look-once version 7 (YOLOv7) and Faster R-CNN. The detection results show the high performance of the proposed method on both simulated and real-measured data without suppressing interferences (e.g., clutter, jamming, and noise). In particular, even if the target is submerged in clutter, the target can still be detected by the proposed method based on the multipath feature.<\/jats:p>","DOI":"10.3390\/rs16244773","type":"journal-article","created":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T09:13:38Z","timestamp":1734945218000},"page":"4773","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Multipath and Deep Learning-Based Detection of Ultra-Low Moving Targets Above the Sea"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7813-5808","authenticated-orcid":false,"given":"Zhaolong","family":"Wang","sequence":"first","affiliation":[{"name":"Air Defense and Antimissile School, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaokuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Air Defense and Antimissile School, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4205-538X","authenticated-orcid":false,"given":"Weike","family":"Feng","sequence":"additional","affiliation":[{"name":"Air Defense and Antimissile School, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Binfeng","family":"Zong","sequence":"additional","affiliation":[{"name":"Air Defense and Antimissile School, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tong","family":"Wang","sequence":"additional","affiliation":[{"name":"Air Defense and Antimissile School, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6209-9462","authenticated-orcid":false,"given":"Cheng","family":"Qi","sequence":"additional","affiliation":[{"name":"Air Defense and Antimissile School, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3415-0800","authenticated-orcid":false,"given":"Xixi","family":"Chen","sequence":"additional","affiliation":[{"name":"Air Defense and Antimissile School, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,21]]},"reference":[{"key":"ref_1","first-page":"3502305","article-title":"A PointNet-Based CFAR Detection Method for Radar Target Detection in Sea Clutter","volume":"21","author":"Chen","year":"2024","journal-title":"IEEE Geosci. 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