Development and application of data mining method for synthetic aperture radar image ship inspection based on big data application technology

Abstract

Synthetic aperture radar belongs to the radar signal working in microwave band, which has the characteristics of strong penetrating performance, large area imaging, all-weather and so on, and is widely used in the civil field and military field. Especially in the background of the information era, synthetic aperture radar imaging technology has developed to different degrees, and the resolution of synthetic aperture radar images has been significantly improved, which is highly valued by the target detection field, and the detection of naval targets through the reasonable use of synthetic aperture radar images has become an important application direction in the field of marine remote sensing. Based on this, this paper analyzes the characteristics of ship targets in SAR images, analyzes the differences between them and optical images from different aspects, and then concentrates on the most common statistical models and prediction methods of clutter analysis in SAR images, proposes the most reasonable way of clutter distribution simulation, and then uses the experimental way to accurately evaluate the complex sea clutter in SAR images, so as to propose the similar characteristics of the ship detection method‥