{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T16:17:01Z","timestamp":1783613821819,"version":"3.55.0"},"reference-count":53,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,24]],"date-time":"2022-04-24T00:00:00Z","timestamp":1650758400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Along with the rapid development of marine radar, and particularly those carried on aircraft, the detection of small-sized targets which pose an increasing threat has become one of the main areas of interest. However, by considering an observation chain from an aircraft (such as a drone) in a maritime environment, with the aim of detecting and tracking of low signal-to-clutter ratio (SCR) targets, one of the important points would be the analysis of the radar system performance according to the radar input parameters, the atmospheric propagation medium, the various sea clutter characterization, and the type of targets (RCS, speed, etc.) in this environment. Therefore, it is necessary to obtain the overall path loss including the anomalous atmospheric environment, gas attenuation, clouds attenuation, rainfall attenuation, and beam scanning loss. To consider atmospheric attenuations, ITU-R models are used. On another side, because of spikes and dynamic variation properties, sea clutter is generally described by the statistical distribution with long tail and by its wider Doppler spectrum. Conventional algorithms such as those based on statistical models, MTI, and MTD processing are often limited, especially for the target of low speed and low RCS. Therefore, sea clutter, including empirical and statistical models available, is considered to estimate and simulate the impact of radar input parameters, targets RCS, and sea state on detection performance. The Doppler frequency of target echo which can be exploited for coherent processing is described by assuming an adequate scenario of observation geometry.<\/jats:p>","DOI":"10.3390\/s22093263","type":"journal-article","created":{"date-parts":[[2022,4,24]],"date-time":"2022-04-24T22:22:41Z","timestamp":1650838961000},"page":"3263","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Analysis of Small Sea-Surface Targets Detection Performance According to Airborne Radar Parameters in Abnormal Weather Environments"],"prefix":"10.3390","volume":"22","author":[{"given":"Hamza","family":"Bounaceur","sequence":"first","affiliation":[{"name":"Lab-STICC UMR CNRS 6285, ENSTA Bretagne, 2 Rue Fran\u00e7ois Verny, 29806 Brest, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8791-0768","authenticated-orcid":false,"given":"Ali","family":"Khenchaf","sequence":"additional","affiliation":[{"name":"Lab-STICC UMR CNRS 6285, ENSTA Bretagne, 2 Rue Fran\u00e7ois Verny, 29806 Brest, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean-Marc","family":"Le Caillec","sequence":"additional","affiliation":[{"name":"Lab-STICC UMR CNRS 6285, IMT Atlantique, 655 Avenue du Technop\u00f4le, 29280 Plouzan\u00e9, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,24]]},"reference":[{"key":"ref_1","first-page":"106430T","article-title":"Optimizing cooperative cognitive search and rescue UAVs","volume":"10643","author":"Rahmes","year":"2018","journal-title":"Proc. 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