School of Electronics and Information Engineering, Beihang University, Beijing 100081, China.
Sensors (Basel). 2018 Nov 19;18(11):4034. doi: 10.3390/s18114034.
Radio frequency interference (RFI) is known to jam synthetic aperture radar (SAR) measurements, severely degrading the SAR imaging quality. The suppression of RFI in SAR echo signals is usually an underdetermined blind source separation problem. In this paper, we propose a novel method for multiclass RFI detection and suppression based on the single shot multibox detector (SSD). First, an echo-interference dataset is established by randomly combining the target signal with various types of RFI in a simulation, and the time⁻frequency form of the dataset is obtained by utilizing the short-time Fourier transform (STFT). Next, the time⁻frequency dataset acts as input data to train the SSD and obtain a network that is capable of detecting, identifying and estimating the interference. Finally, all of the interference signals are exactly reconstructed based on the prediction results of the SSD and mitigated by an adaptive filter. The proposed method can effectively increase the signal-to-interference-noise ratio (SINR) of RFI-contaminated SAR echoes and improve the peak sidelobe ratio (PSLR) after pulse compression. The simulated experimental results validate the effectiveness of the proposed method.
射频干扰（RFI）会干扰合成孔径雷达（SAR）测量，严重降低 SAR 成像质量。SAR 回波信号中的 RFI 抑制通常是一个欠定的盲源分离问题。在本文中，我们提出了一种基于单-shot 多框检测器（SSD）的多类 RFI 检测和抑制的新方法。首先，通过在模拟中随机组合目标信号和各种类型的 RFI 来建立回波干扰数据集，并利用短时傅里叶变换（STFT）得到数据集的时频形式。然后，将时频数据集作为输入数据来训练 SSD，并获得能够检测、识别和估计干扰的网络。最后，基于 SSD 的预测结果，对所有干扰信号进行精确重构，并通过自适应滤波器进行抑制。提出的方法可以有效地提高 RFI 污染的 SAR 回波的信干噪比（SINR），并在脉冲压缩后提高峰值旁瓣比（PSLR）。仿真实验结果验证了所提方法的有效性。
