Range-Doppler Image Interference Detection Based on Fourier-Polar Coordinate Transform for Over-the-Horizon Radar

This paper studies the detection of interference in over-the-horizon (OTH) radar systems, particularly transient interference (TSI) and radio frequency interference (RFI). We introduce a novel interference detection approach that utilizes range-Doppler (RD) image. Traditional techniques of feature extraction is unable to detect some interference. Hence, we develop the Fourier-polar coordinate transform (FPCT) for feature extraction of RD images. Then, the K-Nearest Neighbors (KNN) algorithm is employed to classify the features. Based on FPCT and KNN, our classifier is designed, to classify the RD images into three categories: TSI, RFI, and no interference. In experiments, we simulate our design and traditional feature operators. The results show that our proposed FPCT and classifier achieves higher accuracy than traditional classifiers.