Abstract
Inaccuracies in the observation model of the synthetic aperture radar (SAR) due to inaccuracies of the velocity and position of the platform or atmospheric turbulence cause degradations in reconstructed images which necessitate the use of autofocus algorithms. In this paper we propose a novel signal processing algorithm for joint SAR image formation and autofocus in a synthesis dictionary based sparse representation framework. Proposed algorithm can be applied broadly to scenes that exhibit sparsity with respect to any dictionary. This is done by extending our previously developed sparse representation-based SAR imaging framework to joint SAR image formation and autofocus. To this end, the phase error vector is separated from the unknown phase of the complex-valued back-scattered field. Phase error vector is estimated using a MAP estimator and compensated through an iterative algorithm to produce focused images. We demonstrate the effectiveness of the proposed approach on synthetic and real imagery.
Similar content being viewed by others
References
Wiley, C.A.: Pulsed Doppler radar methods and apparatus. Google Patents (1965)
Jakowatz, C.V., Wahl, D.E., Eichel, P.H., Ghiglia, D.C., Thompson, P.A.: Spotlight-Mode Synthetic Aperture Radar: A Signal Processing Approach, vol. 101. Kluwer, Norwell (1996)
Carrara, W.G., Goodman, R.S., Majewski, R.M.: Spotlight Synthetic Aperture Radar: Signal Processing Algorithms. Artech House, Boston (1995)
Wahl, D., Eichel, P., Ghiglia, D., Jakowatz Jr., C.: Phase gradient autofocus—a robust tool for high resolution SAR phase correction. IEEE Trans. Aerosp. Electron. Syst. 30, 827–835 (1994)
Morrison, R.L., Do, M.N., Munson, D.C.: MCA: a multichannel approach to SAR autofocus. IEEE Trans. Image Process. 18, 840–853 (2009)
Önhon, N.Ö., Çetin, M.: A sparsity-driven approach for joint SAR imaging and phase error correction. IEEE Trans. Image Process. 21, 2075–2088 (2012)
Çetin, M., Karl, W.C.: Feature-enhanced synthetic aperture radar image formation based on nonquadratic regularization. IEEE Trans. Image Process. 10, 623–631 (2001)
Kelly, S., Yaghoobi, M., Davies, M.: Sparsity-based autofocus for undersampled synthetic aperture radar. IEEE Trans. Aerosp. Electron. Syst. 50, 972–986 (2014)
Ügur, S., Arkan, O.: SAR image reconstruction and autofocus by compressed sensing. Digit. Signal Process. 22(6), 923–932 (2012)
Samadi, S., Çetin, M., Masnadi-Shirazi, M.A.: Sparse representation-based synthetic aperture radar imaging. IET Radar Sonar Navig. 5, 182–193 (2011)
Starck, J.L., Elad, M., Donoho, D.L.: Image decomposition via the combination of sparse representations and a variational approach. IEEE Trans. Image Process. 14(10), 1570–1582 (2005)
Donoho, D.L., Johnstone, I.: Ideal spatial adaptation via wavelet shrinkage. Biometrika 81, 425–455 (1994)
Chen, S.S., Donoho, D.L., Saunders, M.A.: Atomic decomposition by basis pursuit. SIAM J. Sci. Comput. 20, 33–61 (1998)
Samadi, S., Çetin, M., Masnadi-Shirazi, M.A. :Sparse signal representation for complex-valued imaging. In: 13th IEEE Digital Signal Processing Workshop, pp. 365–370 (2009)
Elad, M., Bruckstein, A.M.: A generalized uncertainty principle and sparse representation in pairs of bases. IEEE Trans. Inf. Theory 48, 2558–2567 (2002)
Malioutov, D.M., Çetin, M., Willsky, A.S.: Optimal sparse representations in general overcomplete bases. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP’04), pp. ii-793-6 (2004)
Bonnans, J.F., Gilbert, J.C., Lemarechal, C., Sagastizabal, C.A.: Numerical Optimization: Theoretical and Practical Aspects. Springer, Berlin (2006)
Golub, G.H., Van Loan, C.F.: Matrix Computations. JHU Press, Baltimore (2012)
Çetin, M., Karl, W.C., Willsky, A.S.: Feature-preserving regularization method for complex-valued inverse problems with application to coherent imaging. Opt. Eng. 45, 017003-11 (2006)
Batu, O., Çetin, M.: Parameter selection in sparsity-driven SAR imaging. IEEE Trans. Aerosp. Electron. Syst. 47(4), 3040–3050 (2011)
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Hasankhan, M.J., Samadi, S. & Çetin, M. Sparse representation-based algorithm for joint SAR image formation and autofocus. SIViP 11, 589–596 (2017). https://doi.org/10.1007/s11760-016-0998-y
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11760-016-0998-y