Multiclass Radio Frequency Interference Detection and Suppression for SAR Based on the Single Shot MultiBox Detector

Abstract

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.

Mitigation of Radio Frequency Interference in Synthetic Aperture Radar Data: Current Status and Future Trends

“…On the other hand, the artificial learning techniques have proved very successful for various applications in recent years. Initial research show that the introduction of advanced artificial intelligent techniques such as deep learning network perform rather good for interference suppression [101][102][103][104]. After finishing the off-line training step of the artificial neural network from the big data, the on-line detection and mitigation could be realized in a quite efficient way [104].…”

Interference Mitigation for Synthetic Aperture Radar Based on Deep Residual Network

“…In the past few decades, various RFI mitigation methods have been developed to mitigate the influence of RFI on SAR imaging [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. Generally, these interference mitigation algorithms can be divided into two types.…”

“…The other type is nonparametric interference mitigation methods, which mainly design a reasonable filter and separate the interference and useful signal in a specific domain [11][12][13][14][19][20][21][22][23][24][25][26]. Range-spectrum notch filtering is a simple but efficient method for interference mitigation.…”

Hand Gesture Recognition Based on Single-Shot Multibox Detector Deep Learning

“…e Single-Shot Multibox Detector (SSD) further optimizes object detection [23,24]. As compared to Faster R-CNN, SSD is more simple and efficient as it completely eliminates proposal generation subsequent pixel and feature resampling stages, and it also encapsulates all computation in a single network which makes SSD easily trainable and straightforward to integrate into systems [5,[25][26][27][28].…”