Currently, the spaceborne synthetic aperture radar (SAR) system transmits a great deal of data to the ground processing station and generates massive images daily, only a tiny fraction of which contains radio frequency interference (RFI). However, most of the existing RFI detection methods are based on the prior conditions in which the known image contains interference. In fact, it is difficult to learn whether SAR images contain RFIs without prescreening, so it is of great significance to the rapid and real-time screening and detection of RFI in SAR images. This article proposes a method to screen and detect RFI from massive SAR images simultaneously. 1) We construct an approximate RFI-free background image by using the preprocessed time-series SAR images acquired in the past. 2) We generate difference images based on the image change detection method and analyze them by using an adaptive threshold, then calculate the entropy of all difference images to complete the preliminary screening of the RFI-containing). According to the preliminary results, we remove the RFI-containing parts; after reconstructing the background, we repeat step 2 with the images to be detected and obtain the final screening and detection results. Massive experimental results based on Sentinel-1 images validate the performance of the proposed method.

中文翻译：

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海量 SAR 图像中 RFI 的同步筛查和检测：以欧洲 Sentinel-1 为例


目前，星载合成孔径雷达（SAR）系统每天向地面处理站传输大量数据并生成海量图像，其中只有极小部分含有射频干扰（RFI）。然而，现有的RFI检测方法大多基于已知图像存在干扰的先验条件。事实上，在不进行预筛选的情况下很难获知SAR图像是否含有RFI，因此对SAR图像中RFI的快速、实时筛查和检测具有重要意义。本文提出了一种从海量SAR图像中同时筛选和检测RFI的方法。 1）我们利用过去获取的预处理时间序列SAR图像构建近似的无RFI背景图像。 2）基于图像变化检测方法生成差异图像，并使用自适应阈值对其进行分析，然后计算所有差异图像的熵，完成含RFI的初步筛选）。根据初步结果，我们去除含有RFI的部分；重建背景后，对待检测图像重复步骤2，得到最终的筛选和检测结果。基于Sentinel-1图像的大量实验结果验证了该方法的性能。