Title :
A Relationship Between Time-Reversal Imaging and Maximum-Likelihood Scattering Estimation
Author :
Shi, Gang ; Nehorai, Arye
Author_Institution :
Washington Univ., St. Louis
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;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2007.896244