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 ...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.展开更多
Synthetic aperture radar(SAR) is usually sensitive to trajectory deviations that cause serious motion error in the recorded data. In this paper, a coherent range-dependent mapdrift(CRDMD) algorithm is developed to acc...Synthetic aperture radar(SAR) is usually sensitive to trajectory deviations that cause serious motion error in the recorded data. In this paper, a coherent range-dependent mapdrift(CRDMD) algorithm is developed to accommodate the range-variant motion errors. By utilizing the algorithm as an estimate core, robust motion compensation strategy is proposed for unmanned aerial vehicle(UAV) SAR imagery. CRDMD outperforms the conventional map-drift algorithms in both accuracy and efficiency. Real data experiments show that the proposed approach is appropriate for precise motion compensation for UAV SAR.展开更多
文摘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.
基金supported by the Key R&D Program Projects in Hainan Province (ZDY 2019008)the State Key Laboratory of Rail T ransit Engineering Information (SKLK22-08)。
文摘Synthetic aperture radar(SAR) is usually sensitive to trajectory deviations that cause serious motion error in the recorded data. In this paper, a coherent range-dependent mapdrift(CRDMD) algorithm is developed to accommodate the range-variant motion errors. By utilizing the algorithm as an estimate core, robust motion compensation strategy is proposed for unmanned aerial vehicle(UAV) SAR imagery. CRDMD outperforms the conventional map-drift algorithms in both accuracy and efficiency. Real data experiments show that the proposed approach is appropriate for precise motion compensation for UAV SAR.
