High-frequency surface wave radar (HFSWR), as a novel ocean observation radar, enables over-the-horizon, all-weather monitoring of the sea surface, unaffected by the Earth’s curvature. Currently, HFSWR is widely applied in maritime target detection and ocean dynamic parameter measurement, playing a crucial role in both military and civilian domains. During operation, strong sea clutter often overwhelms target echoes, significantly affecting maritime target detection accuracy. Effective suppression of sea clutter is therefore key to improving detection performance. This study leverages the chaotic characteristics of sea clutter to establish a prediction model using radial basis function (RBF) neural networks. By predicting sea clutter and subtracting it from radar echoes in the time domain, effective clutter suppression is achieved. Intelligent optimization algorithms are introduced and improved to optimize the RBF network, enhancing prediction accuracy and further suppressing clutter.
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Taschenbuch. Etat : Neu. Sea Clutter Suppression in High-Frequency Surface Wave Radar | based on Neural Network Models | Shang Shang | Taschenbuch | Englisch | 2025 | Scholars' Press | EAN 9786209172038 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. N° de réf. du vendeur 134294906
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Paperback. Etat : new. Paperback. High-frequency surface wave radar (HFSWR), as a novel ocean observation radar, enables over-the-horizon, all-weather monitoring of the sea surface, unaffected by the Earth's curvature. Currently, HFSWR is widely applied in maritime target detection and ocean dynamic parameter measurement, playing a crucial role in both military and civilian domains. During operation, strong sea clutter often overwhelms target echoes, significantly affecting maritime target detection accuracy. Effective suppression of sea clutter is therefore key to improving detection performance. This study leverages the chaotic characteristics of sea clutter to establish a prediction model using radial basis function (RBF) neural networks. By predicting sea clutter and subtracting it from radar echoes in the time domain, effective clutter suppression is achieved. Intelligent optimization algorithms are introduced and improved to optimize the RBF network, enhancing prediction accuracy and further suppressing clutter. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9786209172038
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -High-frequency surface wave radar (HFSWR), as a novel ocean observation radar, enables over-the-horizon, all-weather monitoring of the sea surface, unaffected by the Earth's curvature. Currently, HFSWR is widely applied in maritime target detection and ocean dynamic parameter measurement, playing a crucial role in both military and civilian domains. During operation, strong sea clutter often overwhelms target echoes, significantly affecting maritime target detection accuracy. Effective suppression of sea clutter is therefore key to improving detection performance. This study leverages the chaotic characteristics of sea clutter to establish a prediction model using radial basis function (RBF) neural networks. By predicting sea clutter and subtracting it from radar echoes in the time domain, effective clutter suppression is achieved. Intelligent optimization algorithms are introduced and improved to optimize the RBF network, enhancing prediction accuracy and further suppressing clutter.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 232 pp. Englisch. N° de réf. du vendeur 9786209172038
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