Inverse Radon transform-based large micromotion target detection algorithm in synthetic aperture radar

Abstract

When the micromotion (MM) target has a large MM amplitude, the bandwidth of the synthetic aperture radar (SAR) azimuth echo will be greater than the pulse repetition frequency (PRF) of SAR. According to Nyquist sampling theorem, spectrum aliasing will occur at this time, and conventional MM target detection and estimation algorithms may lose effect. To solve the problem of large MM target detection with echo bandwidth greater than the PRF, an inverse Radon transform (IRT)-based large MM target detection algorithm is proposed. The study found that the time-frequency (TF) spectrum of large MM target azimuth echo is usually a folded sinusoidal curve. Then we spliced enough identical TF spectrums to restore an intact sinusoidal curve. The intact sinusoidal curve can be mapped into a peak in the parameter space using IRT. Hence, the algorithm can detect large MM target and estimate its parameters accurately. Data processing results prove the effectiveness of the algorithm. At the same time, the performance analysis proves that the operation speed and antinoise performance of the algorithm are better than that of the Hough transform algorithm.