SHI Hongyin, YANG Xiaoyan, ZHOU Qiuxiao, LIAN Qiusheng. SAR Slow Moving Target Imaging Based on Over-Sampling Smooth Algorithm[J]. Chinese Journal of Electronics, 2017, 26(4): 876-882. DOI: 10.1049/cje.2017.06.005
Citation: SHI Hongyin, YANG Xiaoyan, ZHOU Qiuxiao, LIAN Qiusheng. SAR Slow Moving Target Imaging Based on Over-Sampling Smooth Algorithm[J]. Chinese Journal of Electronics, 2017, 26(4): 876-882. DOI: 10.1049/cje.2017.06.005

SAR Slow Moving Target Imaging Based on Over-Sampling Smooth Algorithm

Funds: This work is supported by the National Natural Science Foundation of China (No.61571388, No.61471313), and the Nature Science Foundation of Hebei Province (No.F2016203251).
More Information
  • Received Date: August 26, 2015
  • Revised Date: March 19, 2016
  • Published Date: July 09, 2017
  • A novel Synthetic aperture radar (SAR) signal processing technique has been proposed which refocused slow moving targets based on phase retrieval algorithm. After theoretical derivation, we can get that the raw data Fourier magnitude of slow moving targets is approximate to the stationary ones in the SAR system. By applying the Fourier magnitude of received data to phase retrieval algorithms, the blur and defocusing effect caused by the moving of the targets can be eliminated. The simulated results demonstrate the validity of this algorithm.
  • V.C. Chen and H. Ling, Time-frequency Transforms for Radar Imaging and Signal Analysis, Artech House Inc Boston MA, 2002.
    D.E. Wahl, P.H. Eichel, D.C. Ghiglia, et al., “Phase gradient autofocus—A robust tool for high resolution SAR phase correction”, IEEE Trans. Aerosp. Electron. Syst., Vol.30, No.3, pp.827-835, 1994.
    S. Werness, W. Carrara, L. Joyce, et al., “Moving target imaging algorithm for SAR data”, IEEE Transactions on Aerospace and Electronic Systems, Vol.26, No.1, pp.57-67, 1990.
    P.A.C. Marques and J.M.B. Dias, “Velocity estimation of fast moving targets using a single SAR sensor”, IEEE Transactions on Aerospace and Electronic Systems, Vol.41, No.1, pp.75-89, 2005.
    P.A.C. Marques and J.M.B. Dias, “Moving target processing in SAR spatial domain”, IEEE Transactions on Aerospace and Electronic Systems, Vol.43, No.3, pp.864-874, 2007.
    G. Li, X.G. Xia, J. Xu, et al, “A velocity estimation algorithm of moving targets using single antenna SAR”, IEEE Transactions on Aerospace and Electronic Systems, Vol.45, No.3, pp.1052-1062, 2009.
    S. Barbarossa and A. Farina, “Detection and imaging of moving objects with synthetic aperture radar”, Radar and Signal Processing IEE Proceedings F, Vol.139, No.1, pp.79-97, 1992.
    C. Noviello, G. Fornaro and M. Martorella, “Focused SAR image formation of moving targets based on doppler parameter estimation”, IEEE Transactions on Geoscience and Remote Sening, Vol.53, No.6, pp.3460-3470, 2015.
    R.P. Perry, R.C. Dipietro and R.L. Fante, “SAR maging of moving targets”, IEEE Transaction on Aerospace and Electronic Systems, Vol.35, No.1, pp.188-200, 1999.
    F. Zhou, R. Wu, M. Xing, et al, “Approach for single channel SAR ground moving target imaging and motion parameter estimation”, IET Radar, Sonar and Navigation, Vol.1, No.1, pp.59-66, 2007.
    G. Li, X.G. Xia and Y.N. Peng, “Doppler keystone transform for SAR imaging of moving Targets”, IEEE Geoscience and Remote Sensing Letters, Vol.5, No.4, pp.573-577, 2008.
    N.O. Önhon and M. Çetin, “A sparsity-driven approach for joint SAR imaging and phase error correction”, IEEE Trans. Image Processing, Vol.21, No.4, pp.2075-2088, 2012.
    N. Ö. Önhon and M. Çetin, “SAR moving target imaging in a sparsity-driven framework”, Proc. SPIE Optics Photonics, Wavelets and Sparsity XIV, Vol.8138, pp.813806, 2011.
    Y. Shechtman, Y.C. Eldar, O. Cohen, et al., “Phase retrieval with application to optical imaging”, IEEE Signal Processing Magazine, Vol.32, No.3, pp.87-109, 2015.
    J.R. Fienup, “Reconstruction of an object from the modulus of its Fourier transform,” Optics Letters, Vol.3, No.1, pp.27-29, 1978.
    J.R. Fienup. “Phase retrieval algorithms: A comparison”, Applied Optics, Vol.21, No.15, pp.2758-2769, 1982.
    A. Fannjiang, “Absolute uniqueness of phase retrieval with random illumination”, Inverse Problems, Vol.28, No.7, pp.75008-75027, 2011.
    J.A. Rodriguez, R. Xu, C.C. Chen, et al., “Over-sampling smoothness: An effective algorithm for phase retrieval of noisy diffraction intensities”, Journal of Applied Crystallography, Vol.46, No.2, pp.312-318, 2013.
    E.J. Candes, Y. Eldar, T. Strohmer, et al., “Phase retrieval via matrix completion”, SIAM Journal on Imaging Sciences, Vol.6, No.1, pp.199-225, 2013.
    E.J. Candes, T. Strohmer and V. Voroninski, “Phaselift: Exact and stable signal recovery from magnitude measurements via convex programmin”, Communications on Pure and Applied Mathematics, Vol.66, No.8, pp.1241-1274, 2013.
    Y. Shechtman, A. Beck and Y.C. Eldar, “Gespar: Efficient phase retrieval of sparse signals”, IEEE Trans. Signal Processing, Vol.62, No.4, pp.928-938, 2014.
    G. Franceschetti and R. Lanari, Synthetic Aperture Radar Processing, CRC Press, 1999.
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