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

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