• DocumentCode
    1152096
  • Title

    Contrast maximisation based technique for 2-D ISAR autofocusing

  • Author

    Martorella, M. ; Berizzi, F. ; Haywood, B.

  • Author_Institution
    Dept. of Inf. Eng., Univ. of Pisa, Italy
  • Volume
    152
  • Issue
    4
  • fYear
    2005
  • Firstpage
    253
  • Lastpage
    262
  • Abstract
    An image contrast based algorithm for 2-D ISAR image autofocusing is proposed. The problem of ISAR image autofocusing is formulated analytically by defining geometry and dynamics of the radar-target system and by assuming a mathematical model for the received signal. The image focusing is then achieved by estimating the model parameters through the maximisation of the image contrast. The problem of the maximum search is solved numerically by means of an iterative search method. An algorithm able to produce an accurate initial guess is also developed by using the radon transform. The good accuracy of the initial guess guarantees the convergence of the optimisation problem solution to the global maximum. The performance of the proposed autofocusing technique is tested by comparing it to the point prominent processing (PPP) algorithm, the phase gradient algorithm (PGA) and the image entropy based technique (IEBT), through the use of real data. Results confirm the effectiveness of the proposed algorithm.
  • Keywords
    Radon transforms; focusing; iterative methods; optimisation; parameter estimation; radar imaging; search problems; synthetic aperture radar; 2D ISAR image autofocusing; contrast maximisation based technique; image contrast based algorithm; image entropy based technique; iterative search method; mathematical model; maximum search problem; model parameters estimation; optimisation problem convergence; phase gradient algorithm; point prominent processing algorithm; radar-target system; radon transform;
  • fLanguage
    English
  • Journal_Title
    Radar, Sonar and Navigation, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-2395
  • Type

    jour

  • DOI
    10.1049/ip-rsn:20045123
  • Filename
    1500262