SAR Imaging of Moving Target based on Knowledge-aided Two-dimensional Autofocus
This work addresses defocusing issues in SAR imaging for moving targets, which is an incremental improvement in radar processing.
The paper tackles the problem of defocused moving targets in synthetic aperture radar (SAR) images due to motion uncertainty by proposing a knowledge-aided two-dimensional autofocus method that estimates azimuth phase error and computes residual errors analytically, resulting in improved computational efficiency and estimation accuracy.
Due to uncertainty on target's motion, the range cell migration (RCM) and azimuth phase error (APE) of moving targets can't be completely compensated in synthetic aperture radar (SAR) processing. Therefore, moving targets often appear two-dimensional (2-D) defocused in SAR images. In this paper, a 2-D autofocus method for refocusing defocused moving targets in SAR images is presented. The new method only requires a direct estimate of APE, while the residual 2-D phase error ( or RCM) is computed from the estimated APE by exploiting the analytical relationship between the 2-D phase error ( or RCM) and APE. Because the parameter estimation is performed in the reduced-dimension space by exploiting prior knowledge on phase error structure, the proposed approach offers clear advantages in both computational efficiency and estimation accuracy.