• DocumentCode
    1099755
  • Title

    A Relationship Between Time-Reversal Imaging and Maximum-Likelihood Scattering Estimation

  • Author

    Shi, Gang ; Nehorai, Arye

  • Author_Institution
    Washington Univ., St. Louis
  • Volume
    55
  • Issue
    9
  • fYear
    2007
  • Firstpage
    4707
  • Lastpage
    4711
  • Abstract
    Time-reversal methods have attracted increasing interest recently. The so-called computational time-reversal approach creates an image of the illuminated scene by computing the back-propagated field and is useful for detecting and estimating targets in the scene. In Shi and Nehorai [ldquoMaximum Likelihood Estimation of Point Scatterers for Computational Time-Reversal Imaging,rdquo Communications in Information and Systems, vol. 5, no. 2, pp. 227-256, 2005], we estimated point scatterers by maximum-likelihood estimate (MLE) using the Born-approximated physical model, as well as the Foldy-Lax model. In this correspondence, we further find an explicit relationship between energy-based basic time-reversal imaging and the MLE approach: the time-reversal imaging function differs by only a scaling factor from the likelihood imaging function using the estimated scattering potential when a single-scatterer model is employed. Furthermore, this scaling factor is a function of the imaging position only. We show that, as a result, time-reversal imaging has a near-far problem that tends to produce a weaker image for areas further away from the imaging arrays, whereas the MLE-based image is more balanced. Experimental results confirm this conclusion.
  • Keywords
    image processing; maximum likelihood estimation; object detection; Born-approximated physical model; Foldy-Lax model; illuminated scene; maximum-likelihood scattering estimation; near-far problem; point scatterer; scaling factor; target detection; time-reversal imaging; Acoustic scattering; Application software; Biomedical computing; Biomedical imaging; Electromagnetic scattering; Layout; Maximum likelihood detection; Maximum likelihood estimation; Modeling; Sensor arrays; Maximum-likelihood estimate (MLE); multistatic; near– far problem; time-reversal imaging;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2007.896244
  • Filename
    4291871