Cross-Range Resolution Enhancement for DBS Imaging in a Scan Mode Using Aperture-Extrapolated Sparse Representation

This letter addresses the problem of cross-range superresolution in Doppler beam sharpening (DBS). The coherence of echoes in the azimuth direction and the sparsity of the DBS image in the Doppler domain are fully exploited; thus, a superresolution DBS imaging framework using aperture-extrapolated sparse representation (SR) is proposed. In this framework, aperture extrapolation based on the autoregressive model is utilized to predict the forward and backward information in the azimuth direction, and SR is exploited to extract the Doppler spectrum information. In addition, the resolution ability with different coherent processing intervals is analyzed. The sharpening ratio in this proposed algorithm can be improved by a factor of two or four theoretically in comparison with the conventional DBS imaging method. Experimental results demonstrate that the proposed framework can lead to noticeable performance improvement.

[1]  M. J. Gerry,et al.  A parametric model for synthetic aperture radar measurements , 1999 .

[2]  Joel A. Tropp,et al.  Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit , 2007, IEEE Transactions on Information Theory.

[3]  Inder J. Gupta,et al.  Data extrapolation for high resolution radar imaging , 1994 .

[4]  M. E. Radant The evolution of digital signal processing for airborne radar , 2002 .

[5]  Yan Wu,et al.  A DBS image stitching algorithm based on affine transformation , 2013 .

[6]  Fei Li,et al.  Ground Moving Target Extraction in a Multichannel Wide-Area Surveillance SAR/GMTI System via the Relaxed PCP , 2013, IEEE Geoscience and Remote Sensing Letters.

[7]  Steven Kay,et al.  Modern Spectral Estimation: Theory and Application , 1988 .

[8]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[9]  Teng Long,et al.  A DBS Doppler Centroid Estimation Algorithm Based on Entropy Minimization , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Marco Martorella,et al.  Statistical CLEAN Technique for ISAR Imaging , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Brian W. Zuerndorfer,et al.  Enhanced Imagery Using Spectral-Estimation-Based Techniques , 1997 .

[12]  Delphine Cerutti-Maori,et al.  Wide-Area Traffic Monitoring With the SAR/GMTI System PAMIR , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[13]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[14]  Michael Elad,et al.  From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images , 2009, SIAM Rev..

[15]  Hermann Rohling,et al.  Radar CFAR Thresholding in Clutter and Multiple Target Situations , 1983, IEEE Transactions on Aerospace and Electronic Systems.

[16]  S.M. Kay,et al.  Spectrum analysis—A modern perspective , 1981, Proceedings of the IEEE.