access icon free Image registration for InISAR based on joint translational motion compensation

The registration of inverse synthetic aperture radar (ISAR) images is a key process in interferometric ISAR (InISAR) imaging. According to published literature, there are mainly two solutions for ISAR image registration, one is correlation coefficient based method and the other is parameter estimation of target angular motion. Though some simulation results are effective, defects of these two methods still need to be studied and solved. Different from precedent methods, the authors try new approach for ISAR image registration in this study and better results are obtained. The authors’ new approach is based on joint translational motion compensation, which consists of two steps namely joint range alignment and joint phase autofocus. The first step realises registration along range direction and the second one realises registration along cross-range direction. The new method achieves ISAR image registration along with the translational motion compensation, thus no extra computation is needed. In addition to high computational efficiency, the new method is more precise compared with precedent methods and works well even under strong noise. Simulation results show the advantages of the proposed method in computing efficiency, precision, robustness and practicability.

Inspec keywords: synthetic aperture radar; motion compensation; image registration; radar imaging

Other keywords: cross-range direction; translational motion compensation; ISAR image registration; InISAR; joint phase autofocus; inverse synthetic aperture radar images; joint translational motion compensation; joint range alignment

Subjects: Radar equipment, systems and applications

References

    1. 1)
      • 8. Qingsong, W., Jishuang, Q., Haifeng, H., et al: ‘A method based on integrating real and complex correlation function for InSAR image coregistration’, Acta Geod. Cartographica Sin., 2012, 41, (4), pp. 563569.
    2. 2)
      • 1. Wang, G., Xia, X., Chen Victor, C.: ‘Three-dimensional ISAR imaging of maneuvering targets using three receivers’, IEEE Trans. Image Process., 2001, 10, (3), pp. 436447.
    3. 3)
      • 11. Biao, T., Yang, L., Shiyou, X., et al: ‘Interferometric inverse synthetic aperture radar imaging for space targets based on wideband direct sampling using two antennas’, J. Appl. Remote Sens., 2014, 8, p. 083599.
    4. 4)
      • 10. Stone, H.S., Orchard, M.T., Chang, E.C., et al: ‘A fast direct Fourier-based algorithm for subpixel registration of images’, IEEE Trans. Geosci. Remote Sens., 2001, 39, (10), pp. 22352243.
    5. 5)
      • 15. Wahl, D.E., Eichel, P.H., Ghiglia, D.C., et al: ‘Phase gradient autofocus-a robust tool for high resolution SAR phase correction’, IEEE Trans. Aerosp. Electron. Syst., 1994, 3, (30), pp. 827834.
    6. 6)
      • 3. Liang, H.Q., He, M.Y., Li, N.J., et al: ‘The research of near-field InISAR imaging diagnosis’. Int. Conf. Microwave and Millimeter Wave Technology, 2008, pp. 17731775.
    7. 7)
      • 7. Zhang, Q., Yeo T, S., Du, G., et al: ‘Estimation of three-dimensional motion parameters in interferometric ISAR imaging’, IEEE Trans. Geosci. Remote Sens., 2004, 42, (2), pp. 292300.
    8. 8)
      • 17. Hou, Q.K., Liu, Y., Fan, L.J., et al: ‘Compressed sensing digital receiver and orthogonal reconstructing algorithm for wideband ISAR radar’, Sci. China Inf. Sci., 2015, 58, (10), p. 020302.
    9. 9)
      • 2. Smith B, J., Rock, J.C., Mcfarlin, S.: ‘A synthetic interferometric ISAR technique for developing 3-D signatures’. IEEE Aerospace Conf. Proc., 2003, pp. 10551065.
    10. 10)
      • 14. Itoh T, M., Donohoe, G.W.: ‘Motion compensation for ISAR via CENTROID Tracking’, IEEE Trans. Aerosp. Electron. Syst., 1996, 32, (7), pp. 11911197.
    11. 11)
      • 16. Liu, Y., Hou, Q.K., Xu, S.Y., et al: ‘System distortion analysis and compensation of DIFS signals for wideband imaging radar’, Sci. China Inf. Sci., 2015, 58, (16), p. 020304.
    12. 12)
      • 13. Xiaohui, Q., Alice, H.W.C., Yam, Y.S.: ‘Fast minimum entropy phase compensation for ISAR imaging’, J. Electron. Inf. Technol., 2004, 26, (10), pp. 16561660.
    13. 13)
      • 5. Biao, T., Jiangwei, Z., Shiyou, X., et al: ‘Squint model interferometric ISAR imaging based on respective reference range selection and squint iteration improvement’, IET Radar Sonar Navig., 2015, 9, pp. 13661375.
    14. 14)
      • 6. Biao, T., Na, L., Yang, L., et al: ‘A Novel image registration method for InISAR imaging system’. SPIE Security & Defence 2014, Amsterdam (Netherlands), vol. 9252, 92520U, September 2014.
    15. 15)
      • 12. Li, X., Liu G, S., Ni, J.L.: ‘Autofocusing of ISAR images based on entropy minimization’, IEEE Trans. Aerosp. Electron. Syst., 1999, 35, (4), pp. 12401252.
    16. 16)
      • 4. Stefano, L., Riccardo, M., Stagliano, D., et al: ‘X-band compact low cost multi-channel radar prototype for short range high resolution 3D-InISAR’. 2014 11th European Radar Conf. (EuRAD), Rome, Italy, 2014.
    17. 17)
      • 9. Qiming, Z., Xuetong, X.: ‘A FFT-based complex correlation function method applied to interferometric complex image corregistration’, Acta Gend. Cartegraphica Sin., 2004, 33, (2), pp. 127131.
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