Estimation of High-Frequency Vibration Parameters for Terahertz SAR Imaging Based on FrFT With Combination of QML and RANSAC

High-frequency vibration of motion platform leads to paired echo for synthetic aperture radar (SAR) imaging, especially in terahertz band due its shorter wave length. Different from most existing parameters estimation methods only considering single component high-frequency vibration, this paper a novel method multi-components model is proposed based on fractional Fourier transform (FrFT) with combination quasi-maximum likelihood (QML) and random sample consensus (RANSAC). Based the establishment error echo, instantaneous chirp rate (ICR) firstly estimated by FrFT sliding sub-aperture, followed which are coarsely obtained through spectrum analysis least square (LS) regression. To further refine estimates, QML developed compensating deviation both caused frequency leakage propagation effects one-dimensional search over frequency. Meanwhile, RANSAC adopted avoiding outlier ICR estimates LS regression, at low signal-to-noise ratio (SNR). Thus, refinement strategy developed, whose utilization improves accuracy parameters. Finally, SAR (THz-SAR) imaging effectively suppressed method, high-quality THz-SAR results achieved. Both simulations used verify validity method. The simulation show that has higher even SNR.