Motion compensation is a key step for inverse synthetic aperture radar (ISAR) imaging. Many algorithms have been proposed. The rank one phase estimation (ROPE) algorithm is a good estimator for phase error widely used...Motion compensation is a key step for inverse synthetic aperture radar (ISAR) imaging. Many algorithms have been proposed. The rank one phase estimation (ROPE) algorithm is a good estimator for phase error widely used in SAR. The ROPE algorithm is used in ISAR phase compensation and the concrete implementation steps are presented. Subsequently, the performance of ROPE is analyzed. For ISAR data that fit the ROPE algorithm model, an excellent compensation effect can be obtained with high computation efficiency. Finally, ISAR real data are processed with ROPE and its imaging result is compared with that obtained by the modified Doppler centroid tracking (MDCT) method, which is a robust and good estimator in ISAR phase compensation.展开更多
Inverse synthetic aperture radar(ISAR)imaging of the target with the non-rigid body is very important in the field of radar signal processing.In this paper,a motion compensation method combined with the preprocessing ...Inverse synthetic aperture radar(ISAR)imaging of the target with the non-rigid body is very important in the field of radar signal processing.In this paper,a motion compensation method combined with the preprocessing and global technique is proposed to reduce the influence of micro-motion components in the fast time domain,and the micro-Doppler(m-D)signal in the slow time domain is separated by the improved complex-valued empirical-mode decomposition(CEMD)algorithm,which makes the m-D signal more effectively distinguishable from the signal for the main body by translating the target to the Doppler center.Then,a better focused ISAR image of the target with the non-rigid body can be obtained consequently.Results of the simulated and raw data demonstrate the effectiveness of the algorithm.展开更多
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
As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A ph...As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.展开更多
文摘Motion compensation is a key step for inverse synthetic aperture radar (ISAR) imaging. Many algorithms have been proposed. The rank one phase estimation (ROPE) algorithm is a good estimator for phase error widely used in SAR. The ROPE algorithm is used in ISAR phase compensation and the concrete implementation steps are presented. Subsequently, the performance of ROPE is analyzed. For ISAR data that fit the ROPE algorithm model, an excellent compensation effect can be obtained with high computation efficiency. Finally, ISAR real data are processed with ROPE and its imaging result is compared with that obtained by the modified Doppler centroid tracking (MDCT) method, which is a robust and good estimator in ISAR phase compensation.
基金supported by the National Natural Science Foundation of China(61871146)the Fundamental Research Funds for the Central Universitiesthe State Key Laboratory of Millimeter Waves(K202022)。
文摘Inverse synthetic aperture radar(ISAR)imaging of the target with the non-rigid body is very important in the field of radar signal processing.In this paper,a motion compensation method combined with the preprocessing and global technique is proposed to reduce the influence of micro-motion components in the fast time domain,and the micro-Doppler(m-D)signal in the slow time domain is separated by the improved complex-valued empirical-mode decomposition(CEMD)algorithm,which makes the m-D signal more effectively distinguishable from the signal for the main body by translating the target to the Doppler center.Then,a better focused ISAR image of the target with the non-rigid body can be obtained consequently.Results of the simulated and raw data demonstrate the effectiveness of the algorithm.
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 National Natural Science Foundation of China(61071165)the Program for NewCentury Excellent Talents in University(NCET-09-0069)the Defense Industrial Technology Development Program(B2520110008)~~
文摘As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.
