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dc.contributor.authorMachado-Fernández, José Raúl
dc.contributor.authorBacallao-Vidal, Jesús Concepción
dc.contributor.authorTorres Martinez, Shirley
dc.date2017-06
dc.date.accessioned2021-08-26T11:59:27Z
dc.date.available2021-08-26T11:59:27Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/11742
dc.description.abstractOceanic and coastal radars operation is affected because the targets information is received mixed with and undesired contribution called sea clutter. Specifically, the popular CA-CFAR processor is incapable of maintaining its design false alarm probability when facing clutter with statistical variations. In opposition to the classic alternative suggesting the use of a fixed adjustment factor, the authors propose a modification of the CA- CFAR scheme where the factor is constantly corrected according on the background signal statistical changes. Mathematically translated as a variation in the shape parameter of the clutter distribution, the background signal changes were simulated through the Weibull, Log-Normal and K distributions, deriving expressions which allow choosing an appropriate factor for each possible statistical state. The investigation contributes to the improvement of radar detection by suggesting the application of an adaptive scheme which assumes the clutter shape parameter is known a priori. The offered mathematical expressions are valid for three false alarm probabilities and several windows sizes, covering also a wide range of clutter conditions.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 4, nº 4
dc.relation.urihttps://ijimai.org/journal/bibcite/reference/2600es_ES
dc.rightsopenAccesses_ES
dc.subjectradar clutteres_ES
dc.subjectCFARes_ES
dc.subjectfalse alarm probabilites_ES
dc.subjectradar detectors performancees_ES
dc.subjectIJIMAIes_ES
dc.titleCA-CFAR Adjustment Factor Correction with a priori Knowledge of the Clutter Distribution Shape Parameteres_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttps://doi.org/10.9781/ijimai.2017.441


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