IMPACT ANALYSIS OF RADIO FREQUENCY INTERFERENCE ON SAR IMAGE SHIP DETECTION BASED ON DEEP LEARNING

In this paper, attention was paid to the impacts of RFI (Radio Frequency Interference) on SAR (Synthetic Aperture Radar) image ship detection with a proposed net structure based on deep learning. The RFI of different intensities can destroy the quality of SAR images, and pose difficulty for ship detection in marine environment. We acquired the dataset that contains numerous sample slices from two satellites, and took different ranges of SIR (Signal to Interference Ratio) to evaluate the robustness of the framework on the conditions. The experimental results show that the SAR images corrupted by RFI can affect the detection performance greatly. And it may provide suggest to researchers to conduct the interference properly when using the deep learning algorithm to monitor the ships in SAR images.