摘要
MOtion COmpensation(MOCO) is an essential step in high resolution airborne Synthetic Aperture Radar(SAR) imaging. Generally, a reference altitude level is assumed and external Digital Elevation Model(DEM) is required for the scene topography heavily varied. To overcome the shortcoming, we propose a MOCO method based on Phase Gradient Autofocus(PGA) which can obtain well focused images without DEM. In the implementation, we first compensate the normal range-invariant term. Then the data are divided into strips in range-compressed domain and PGA is applied to each substrip to extract the phase errors. Finally, the phase error surface is obtained using interpolation and then compensated. Real airborne SAR data of a UAV-SAR system experiments and comparisons demonstrate the validity and effectiveness of the proposed algorithm. The results show that our algorithm is effective.
MOtion COmpensation （MOCO） is an essential step in high resolution airborne Synthetic Aperture Radar （SAR） imaging.Generally,a reference altitude level is assumed and external Digital Elevation Model （DEM） is required for the scene topography heavily varied.To overcome the shortcoming,we propose a MOCO method based on Phase Gradient Autofocus （PGA） which can obtain well focused images without DEM.In the implementation,we first compensate the normal range-invariant term.Then the data are divided into strips in range-compressed domain and PGA is applied to each substrip to extract the phase errors.Finally,the phase error surface is obtained using interpolation and then compensated.Real airborne SAR data of a UAV-SAR system experiments and comparisons demonstrate the validity and effectiveness of the proposed algorithm.The results show that our algorithm is effective.
