{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T05:14:29Z","timestamp":1776402869234,"version":"3.51.2"},"reference-count":36,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,4,7]],"date-time":"2023-04-07T00:00:00Z","timestamp":1680825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Research, Innovation, and Digitization, CNCS\u2014UEFISCDI","award":["PN-III-P4-PCE-2021-0015"],"award-info":[{"award-number":["PN-III-P4-PCE-2021-0015"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMSE"],"abstract":"<jats:p>Maritime unmanned systems (MUS) have gained widespread usage in a diverse range of hydrographic survey activities, including harbor\/port surveys, beach and coastline monitoring, environmental assessment, and military operations. The present article explains a validated, rapid, and reliable technique for processing hydrographic data that was obtained via an autonomous hydrographic survey, and which was executed by a prototype unmanned surface vessel (USV) belonging to the Unmanned Survey Solutions (USS) corporation. The experimentation was part of the annual Multinational Exercise Robotic Experimentation and Prototyping that was augmented by Maritime Unmanned Systems 22 (REPMUS22), which was held in the national waters of Portugal. The main objective of this experimentation was to assess the underwater environment over an ocean beach for an amphibious landing exercise. Moreover, the integration of the multibeam system with the autonomous prototype vessel was assessed. A short comparison between the USV survey and a traditional vessel multibeam survey is presented, whereby the advantages of performing an autonomous survey operation near the coastline is emphasized. A correlation between a known multibeam processing technique and the dissemination of a rapid but consistent product for operational use is described, highlighting the applicability of the technique for the data collected from small experimental platforms. Moreover, this study outlines the relationship between the particular errors observed in autonomous small vehicles and in conventional data processing methods. The resultant cartographic outputs from the hydrographic survey are presented, emphasizing the specific inaccuracies within the raw data and the suitability of distinct hydrographic products for various user domains.<\/jats:p>","DOI":"10.3390\/jmse11040799","type":"journal-article","created":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T03:49:29Z","timestamp":1681098569000},"page":"799","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Autonomous Shallow Water Hydrographic Survey Using a Proto-Type USV"],"prefix":"10.3390","volume":"11","author":[{"given":"Lauren\u021biu-Florin","family":"Constantinoiu","sequence":"first","affiliation":[{"name":"NATO Maritime Geospatial, Meteorological and Oceanographic Centre of Excellence, 1249-093 Lisbon, Portugal"},{"name":"Department of Mechanical Engineering, Faculty of Engineering, \u201cDun\u0103rea de Jos\u201d University of Galati, 800008 Galati, Romania"}]},{"given":"Mariana","family":"Bernardino","sequence":"additional","affiliation":[{"name":"Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior T\u00e9cnico (IST), 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6899-8442","authenticated-orcid":false,"given":"Eugen","family":"Rusu","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Faculty of Engineering, \u201cDun\u0103rea de Jos\u201d University of Galati, 800008 Galati, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.egyr.2022.10.248","article-title":"A Novel Method Based on Artificial Neural Networks for Selecting the Most Appropriate Locations of the Offshore Wind Farms","volume":"8","author":"Marin","year":"2022","journal-title":"Energy Rep."},{"key":"ref_2","unstructured":"Leder, N., and Leder, T.A. 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