Azimuth Motion Compensation With Improved Subaperture Algorithm for Airborne SAR Imaging

Conventional motion compensation (MOCO) under beam-center approximation is usually insufficient to correct severe track deviations for high-resolution synthetic aperture radar imaging. In this paper, a novel MOCO approach is developed for correction of the azimuth-variant motion errors by exploiting a precise angle-to-Doppler relationship within subapertures. The corruption from the residual motion errors to the angle-to-Doppler mapping is investigated and overcome by a compensation scheme of the scaled Fourier transform. Inheriting the high efficiency, the proposed azimuth MOCO approach has dramatically improved precision over the conventional subaperture MOCO method by reducing high side-lobe peaks of the point spread function. Extensive comparisons with other MOCO algorithms are given to show the superiority of the proposed algorithm. Moreover, real-data experiments are provided for a clear demonstration of our proposed approach.

[1]  F. Rocca,et al.  SAR data focusing using seismic migration techniques , 1991 .

[2]  Riccardo Lanari A new method for the compensation of the SAR range cell migration based on the chirp z-transform , 1995, IEEE Trans. Geosci. Remote. Sens..

[3]  R. Keith Raney,et al.  Precision SAR processing using chirp scaling , 1994, IEEE Trans. Geosci. Remote. Sens..

[4]  Alberto Moreira,et al.  Airborne SAR processing of highly squinted data using a chirp scaling approach with integrated motion compensation , 1994, IEEE Trans. Geosci. Remote. Sens..

[5]  Giorgio Franceschetti,et al.  On center-beam approximation in SAR motion compensation , 2006, IEEE Geoscience and Remote Sensing Letters.

[6]  Rolf Scheiber,et al.  Precise topography- and aperture-dependent motion compensation for airborne SAR , 2005, IEEE Geoscience and Remote Sensing Letters.

[7]  X. Zheng,et al.  A Novel Algorithm for Wide Beam SAR Motion Compensation Based on Frequency Division , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[8]  Wei Song,et al.  Comparison of two-step and one-step motion compensation algorithms for airborne synthetic aperture radar , 2015 .

[9]  Josef Mittermayer,et al.  Sub-aperture algorithm for motion compensation improvement in wide-beam SAR data processing , 2001 .

[10]  Jordi J. Mallorquí,et al.  Topography-dependent motion compensation for repeat-pass interferometric SAR systems , 2005, IEEE Geoscience and Remote Sensing Letters.

[11]  Ian G. Cumming,et al.  Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation , 2005 .

[12]  Alberto Moreira,et al.  Extended wavenumber-domain synthetic aperture radar focusing with integrated motion compensation , 2006 .

[13]  Mengdao Xing,et al.  The Polar Format Imaging Algorithm Based on Double Chirp-Z Transforms , 2008, IEEE Geoscience and Remote Sensing Letters.

[14]  Mehrdad Soumekh,et al.  Synthetic Aperture Radar Signal Processing with MATLAB Algorithms , 1999 .

[15]  Gianfranco Fornaro,et al.  Azimuth-to-Frequency Mapping in Airborne SAR Data Corrupted by Uncompensated Motion Errors , 2013, IEEE Geoscience and Remote Sensing Letters.

[16]  Chibiao Ding,et al.  Precise Focusing of Airborne SAR Data With Wide Apertures Large Trajectory Deviations: A Chirp Modulated Back-Projection Approach , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Jordi J. Mallorquí,et al.  Comparison of Topography- and Aperture-Dependent Motion Compensation Algorithms for Airborne SAR , 2007, IEEE Geoscience and Remote Sensing Letters.