{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:29:31Z","timestamp":1772252971716,"version":"3.50.1"},"reference-count":19,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,10]],"date-time":"2019-07-10T00:00:00Z","timestamp":1562716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In this paper, we propose a novel strategy to estimate the micro-motion (m-m) of ships from synthetic aperture radar (SAR) images. To this end, observe that the problem of motion and m-m detection of targets is usually solved using synthetic aperture radar (SAR) along-track interferometry through two radars spatially separated by a baseline along the azimuth direction. The approach proposed in this paper for m-m estimation of ships, occupying thousands of pixels, processes the information generated during the coregistration of several re-synthesized time-domain and not overlapped Doppler sub-apertures. Specifically, the SAR products are generated by splitting the raw data according to a temporally small baseline using one single wide-band staring spotlight (ST) SAR image. The predominant vibrational modes of different ships are then estimated. The performance analysis is conducted on one ST SAR image recorded by COSMO-SkyMed satellite system. Finally, the newly proposed approach paves the way for application to the surveillance of land-based industry activities.<\/jats:p>","DOI":"10.3390\/rs11141637","type":"journal-article","created":{"date-parts":[[2019,7,10]],"date-time":"2019-07-10T11:56:51Z","timestamp":1562759811000},"page":"1637","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Micro-Motion Estimation of Maritime Targets Using Pixel Tracking in Cosmo-Skymed Synthetic Aperture Radar Data\u2014An Operative Assessment"],"prefix":"10.3390","volume":"11","author":[{"given":"Filippo","family":"Biondi","sequence":"first","affiliation":[{"name":"Electromagnetic Laboratory, Engineering Faculty, University of L\u2019Aquila, 67100 L\u2019Aquila, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2463-8733","authenticated-orcid":false,"given":"Pia","family":"Addabbo","sequence":"additional","affiliation":[{"name":"Science and Technology for Transportations Faculty, Universit\u00e0 degli Studi \u201cGiustino Fortunato\u201d, viale Raffale Delcogliano, 12, 82100 Benevento, Italy"}]},{"given":"Danilo","family":"Orlando","sequence":"additional","affiliation":[{"name":"Engineering Faculty, Universit\u00e0 degli Studi \u201cNiccol\u00f2 Cusano\u201d, Via Don Carlo Gnocchi, 3, 00166 Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6665-693X","authenticated-orcid":false,"given":"Carmine","family":"Clemente","sequence":"additional","affiliation":[{"name":"Centre for Signal and Image Processing, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Filippo, B. 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