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RSS FeedsRemote Sensing, Vol. 11, Pages 563: Extension of Ship Wake Detectability Model for Non-Linear Influences of Parameters Using Satellite Based X-Band Synthetic Aperture Radar (Remote Sensing)

 
 

7 march 2019 20:02:24

 
Remote Sensing, Vol. 11, Pages 563: Extension of Ship Wake Detectability Model for Non-Linear Influences of Parameters Using Satellite Based X-Band Synthetic Aperture Radar (Remote Sensing)
 


The physics of the imaging mechanism underlying the emergence of ship wakes in Synthetic Aperture Radar (SAR) images has been studied in the past by many researchers providing a well-understood theory. Therefore, many publications describe how well ship wakes are detectable on SAR under the influence of different environmental conditions like sea state or local wind, ship properties like ship speed or ship heading, and image acquisition parameters like incidence angle or satellite heading. The increased imaging capabilities of current satellite SAR missions facilitate the collection of large datasets of moving vessels. Such a large dataset of high resolution TerraSAR-X acquisitions now enables the quantitative analysis of the previously formulated theory about the detectability of ship wakes using real data. In this paper we propose an extension of our wake detectability model by using a non-linear basis which allows consideration of all the influencing parameters simultaneously. Such an approach provides new insights and a better understanding of the non-linear influence of parameters on the wake detectability and their interdependencies can now be represented. The results show that the non-linear, interdependent influence of the different influencing parameters on the detectability of wakes matches well to the oceanographic expectations published in the past. Also possible applications of the model for the extraction of missing parameters and automatic for wake detection systems are demonstrated.


 
46 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 11, Pages 564: Airborne SAR Imaging Algorithm for Ocean Waves Based on Optimum Focus Setting (Remote Sensing)
Remote Sensing, Vol. 11, Pages 562: A Comparison of Three Sediment Acoustic Models Using Bayesian Inversion and Model Selection Techniques (Remote Sensing)
 
 
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