{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:34:51Z","timestamp":1760232891585,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T00:00:00Z","timestamp":1670371200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Postdoctoral Science Foundation of China","award":["2019M661508","2019JQ-497","201920096001"],"award-info":[{"award-number":["2019M661508","2019JQ-497","201920096001"]}]},{"name":"Shaanxi Provincial Fund Youth Project of China","award":["2019M661508","2019JQ-497","201920096001"],"award-info":[{"award-number":["2019M661508","2019JQ-497","201920096001"]}]},{"DOI":"10.13039\/501100012130","name":"Aviation Science Fund of China","doi-asserted-by":"publisher","award":["2019M661508","2019JQ-497","201920096001"],"award-info":[{"award-number":["2019M661508","2019JQ-497","201920096001"]}],"id":[{"id":"10.13039\/501100012130","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Translational motion compensation is a prerequisite of inverse synthetic aperture radar (ISAR) imaging. Translational motion compensation for datasets with low signal-to-noise ratio (SNR) is important but challenging. In this work, we proposed a noise-robust translational motion compensation method based on high-order local polynomial transform\u2013generalized scaled Fourier transform (HLPT-GSCFT). We first model the translational motion as a fourth-order polynomial according to order-of-magnitude analysis, and then design HLPT-GSCFT for translation parameter estimation and parametric translational motion compensation. Specifically, HLPT is designed to estimate the acceleration and third-order acceleration of the translational motion and GSCFT is introduced to estimate the second-order acceleration. Both HLPT and GSCFT have a strong ability for cross-term suppression. In addition, we use a minimum weighted entropy algorithm to estimate the velocity of the translational motion, which can improve the noise robustness of the parameter estimation. Experimental results based on a measured dataset prove that the proposed method is effective and noise-robust.<\/jats:p>","DOI":"10.3390\/rs14246201","type":"journal-article","created":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T06:22:18Z","timestamp":1670394138000},"page":"6201","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Noise-Robust ISAR Translational Motion Compensation via HLPT-GSCFT"],"prefix":"10.3390","volume":"14","author":[{"given":"Fengkai","family":"Liu","sequence":"first","affiliation":[{"name":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710051, China"}]},{"given":"Darong","family":"Huang","sequence":"additional","affiliation":[{"name":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710051, China"}]},{"given":"Xinrong","family":"Guo","sequence":"additional","affiliation":[{"name":"Science College, Armed Police Engineering University, Xi\u2019an 710051, China"}]},{"given":"Cunqian","family":"Feng","sequence":"additional","affiliation":[{"name":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710051, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1109\/TAES.1980.308873","article-title":"Target-motion-induced radar imaging","volume":"16","author":"Chen","year":"1980","journal-title":"IEEE Trans. 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