The ship geometric parameter extraction is an essential basis for the marine target detection and classification for the Synthetic Aperture Radar(SAR) images. With the assistance of the ground true value sample of the marine target size, the improvement of the geometric dimension extraction can be achieved by the parameter optimization and regression, as verified in TerraSAR-X datasets. Taking into consideration of the typical characteristics of the dual-polarization for the sentinel-1 products, this paper explores the usefulness of the dual-polarization fusion information. Based on the OpenSARShip, firstly we utilize a two-dimensional filter method for image processing. The parameters in the image processing are optimized by a cross-entropy method based on the large dataset. Next, with the preliminary extraction results, we combine the information from the sensors, the environment and the target, and especially the information from the dual-polarization. We employ a multiple linear regression model to obtain the precise physical dimensions. The size extraction performance by the dual-polarization fusion information is much better than merely using the single-polarization information, which proves the usefulness of the dual polarization information.

Synthetic Aperture Radar(SAR)  /  Sentinel-1  /  OpenSARShip  /  marine target  /  geometric parameter extraction  /  dual-polarization