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Use of Genetic Algorithms for Contrast and Entropy Optimization in ISAR Autofocusing

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Abstract

Image contrast maximization and entropy minimization are two commonly used techniques for ISAR image autofocusing. When the signal phase history due to the target radial motion has to be approximated with high order polynomial models, classic optimization techniques fail when attempting to either maximize the image contrast or minimize the image entropy. In this paper a solution of this problem is proposed by using genetic algorithms. The performances of the new algorithms that make use of genetic algorithms overcome the problem with previous implementations based on deterministic approaches. Tests on real data of airplanes and ships confirm the insight.

References

  1. 1.

    Walker JL: Range-doppler imaging of rotating objects. IEEE Transactions on Aerospace and Electronic Systems 1980, 16: 23–52.

  2. 2.

    Ausherman DA, Kozma A, Walker JL, Jones HM, Poggio EC: Developments in radar imaging. IEEE Transactions on Aerospace and Electronic Systems 1984, 20(4):363–400.

  3. 3.

    Carrara WC, Goodman RS, Majewsky RM: Spotlight Synthetic Aperture Radar: Signal Processing Algorithms. Artech House, Boston, Mass, USA; 1995.

  4. 4.

    Wehner DR: High Resolution Radar. Artech House, Norwood, Mass, USA; 1995.

  5. 5.

    Berizzi F, Corsini G: Autofocusing of inverse synthetic aperture radar images using contrast optimisation. IEEE Transaction on Aerospace and Electronic System 1996, 32(3):1185–1191.

  6. 6.

    Martorella M, Haywood B, Berizzi F, Dalle Mese E: Performance analysis of an ISAR contrast based autofocusing algorithm using real data. Proceedings of IEE Radar Conference, September 2003, Adelaide, Australia 200–205.

  7. 7.

    Xi L, Giosui L, Ni J: Autofocusing of ISAR images based on entropy minimisation. IEEE Transactions on Aerospace and Electronic Systems 1999, 35(4):1240–1252. 10.1109/7.805442

  8. 8.

    Haywood B, Evans RJ: Motion compensation for ISAR imaging. Proceedings of the IEEE Australian Symposium on Signal Processing and Applications (ASSPA '89), April 1989, Adelaide, Australia 113–117.

  9. 9.

    Li J, Wu R, Chen VC: Robust autofocus algorithm for ISAR imaging of moving targets. IEEE Transactions on Aerospace and Electronic Systems 2001, 37(3):1056–1069. 10.1109/7.953256

  10. 10.

    Haiqing W, Grenier D, Delisle GY, Da-Gang F: Translational motion compensation in ISAR image processing. IEEE Transactions on Image Processing 1995, 4(11):1561–1571. 10.1109/83.469937

  11. 11.

    Wang Y, Ling H, Chen VC: ISAR motion compensation via adaptive joint time-frequency technique. IEEE Transactions on Aerospace and Electronic Systems 1998, 34(2):670–677. 10.1109/7.670350

  12. 12.

    Choi I-S, Cho B-L, Kim H-T: ISAR motion compensation using evolutionary adaptive wavelet transform. IEE Proceedings on Radar, Sonar and Navigation 2003, 150(4):229–233. 10.1049/ip-rsn:20030639

  13. 13.

    Li J, Ling H: Use of genetic algorithms in ISAR imaging of targets with higher order motions. IEEE Transactions on Aerospace and Electronic System 2002, 39: 343–351.

  14. 14.

    Polak E: Optimization: Algorithms and Consistent Approximations, Applied Mathematical Sciences. Volume 124. Springer, New York, NY, USA; 1997.

  15. 15.

    Nelder JA, Mead R: A simplex method for function minimisation. Computer Journal 1965, 7: 308–313.

  16. 16.

    Holland J: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, Mich, USA; 1975.

  17. 17.

    Michalewicz Z: Genetic Algorithms + Data Structures = Evolution Programs. Springer, New York, NY, USA; 1994.

  18. 18.

    Houck CR, Joines JA, Kay MG: A genetic algorithm for function optimization: a MATLAB implementation. North Carolina State University, https://doi.org/www.ie.ncsu.edu/mirage/GAToolBox/gaot/

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Correspondence to Marco Martorella.

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Martorella, M., Berizzi, F. & Bruscoli, S. Use of Genetic Algorithms for Contrast and Entropy Optimization in ISAR Autofocusing. EURASIP J. Adv. Signal Process. 2006, 087298 (2006) doi:10.1155/ASP/2006/87298

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Keywords

  • Entropy
  • Genetic Algorithm
  • Image Contrast
  • Polynomial Model
  • Signal Phase