High-Quality Airborne Terahertz Video SAR Imaging Based on Echo-Driven Robust Motion Compensation
Lei Fan, Hongqiang Wang, Qi Yang, Bin Deng
Abstract
Airborne terahertz video synthetic aperture radar (THz-ViSAR) exhibits excellent superiorities in the dynamic situation awareness and moving targets detection. However, limited by the recording precision of the inertial navigation system (INS) or global positioning system (GPS), data-driven motion compensation (MOCO) methods are challenging to eliminate motion errors for THz band. Particularly, platform vibrations that are previously negligible in the microwave band, become non-negligible, drastically degrading the focusing performance. To conquer aforementioned problems, this paper proposes an echo-driven robust MOCO framework suited for THz-ViSAR. First, the airborne motion error model (MED) is re-derived and corresponding effects are analyzed in detail. Based on the derived MED, two parts are required to estimate from the echo: radial errors and vibration errors. Thus, a forward estimation of candidate signal of interests (SoIs) is proposed based on local peaks of the average range profile and the prominence. For each candidate, radial and vibration errors are estimated from the unwrapped phase of the SoI via the polynomial and multi-component sinusoidal fitting in turn. Finally, MOCO functions are constructed and evaluated based on the image entropy and image contrast, which determines the optimal SoI. Airborne field experiments are carried out to validate the effectiveness and practicability of the proposed method.