A Novel Strategy for Radar Imaging Based on Compressive Sensing

This paper aims at introducing the recent theory of compressive sensing to radar imaging systems in order to retrieve the imaged scene with better resolution and a reduced amount of collected samples. As a result of the application of the alternative imaging technique proposed, the use of matched filtering is avoided and the effect of its sidelobes in the images is drastically diminished. Furthermore, the amount of data to be stacked in the sensor and then downlinked to the ground station is meaningfully lower. This permits a more efficient management of resources.

[1]  S. Quegan,et al.  Understanding Synthetic Aperture Radar Images , 1998 .

[2]  J.-E. Nilsson,et al.  Radar with separated subarray antennas , 2003, 2003 Proceedings of the International Conference on Radar (IEEE Cat. No.03EX695).

[3]  Alberto Moreira,et al.  A comparison of several algorithms for SAR raw data compression , 1995, IEEE Trans. Geosci. Remote. Sens..

[4]  Michael W. Marcellin,et al.  Compression of synthetic aperture radar video phase history data using trellis-coded quantization techniques , 1999, IEEE Trans. Geosci. Remote. Sens..

[5]  R. Baraniuk,et al.  Compressive Radar Imaging , 2007, 2007 IEEE Radar Conference.

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

[7]  Felix J. Herrmann,et al.  Non-parametric seismic data recovery with curvelet frames , 2008 .

[8]  R. Bamler,et al.  Synthetic aperture radar interferometry , 1998 .

[9]  Rebecca Willett,et al.  Multiscale reconstruction for computational spectral imaging , 2007, Electronic Imaging.

[10]  Emmanuel J. Candès,et al.  Decoding by linear programming , 2005, IEEE Transactions on Information Theory.

[11]  Kush R. Varshney,et al.  Sparse Representation in Structured Dictionaries With Application to Synthetic Aperture Radar , 2008, IEEE Transactions on Signal Processing.

[12]  J. Romberg,et al.  Imaging via Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[13]  T. Blumensath,et al.  Fast Encoding of Synthetic Aperture Radar Raw Data using Compressed Sensing , 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.

[14]  Stéphane Mallat,et al.  Matching pursuits with time-frequency dictionaries , 1993, IEEE Trans. Signal Process..

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

[16]  Bhaskar D. Rao,et al.  Sparse channel estimation via matching pursuit with application to equalization , 2002, IEEE Trans. Commun..

[17]  Michael A. Saunders,et al.  Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..

[18]  I. Corbella,et al.  MIRAS imaging validation , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[19]  F. Ulaby,et al.  Radar polarimetry for geoscience applications , 1990 .

[20]  D. Donoho,et al.  Sparse MRI: The application of compressed sensing for rapid MR imaging , 2007, Magnetic resonance in medicine.

[21]  Ian G. Cumming,et al.  ENVISAT ASAR data reduction: impact on SAR interferometry , 1998, IEEE Trans. Geosci. Remote. Sens..

[22]  Yaakov Tsaig,et al.  Fast Solution of $\ell _{1}$ -Norm Minimization Problems When the Solution May Be Sparse , 2008, IEEE Transactions on Information Theory.

[23]  Yaakov Tsaig,et al.  Extensions of compressed sensing , 2006, Signal Process..

[24]  Emmanuel J. Candès,et al.  Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? , 2004, IEEE Transactions on Information Theory.

[25]  Jean-Marie Nicolas,et al.  Homomorphic wavelet transform and new subband statistics models for SAR image compression , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

[26]  John C. Curlander,et al.  Synthetic Aperture Radar: Systems and Signal Processing , 1991 .