Synthetic Aperture Radar Autofocus Based On Cross Relation Approach

Synthetic Aperture Radar (SAR) imaging can suffer distortion in the presence of phase errors in the acquired signal data caused by the non-ideal platform motion trajectory. Autofocus algorithms are used to remove the undesired phase error through signal processing techniques. Multi-channel convolution model of the SAR autofocus problem is established on the condition that phase error is range-independent. Then a new non-iterative autofocus algorithm is proposed based on cross correlation approach. The proposed autofocus algorithm can directly acquire the ideal SAR echo data without the estimation of phase error. Experimental results using the real SAR images demonstrate the validity of the proposed autofocus algorithm.