Statistics and Data Science Seminar
Gang Shi
Electrical & Computer Engineer, UIC
Maximum Likelihood Estimation of Point Scatterers for Computational Time-reversal Imaging
Abstract: We present a statistical framework for the fixed-frequency computational
time-reversal imaging problem assuming point scatterers in a known background
medium. Our statistical measurement models are based on the physical models of
the multistatic response matrix, the distorted wave Born approximation and
Foldy-Lax multiple scattering models. We develop maximum likelihood (ML)
estimators of the locations and reflection parameters of the scatterers. Using a
simplified single-scatterer model, we also propose a likelihood time-reversal
imaging technique which is suboptimal but computationally efficient and can be
used to initialize the ML estimation. We generalize the fixed-frequency
likelihood imaging to multiple frequencies, and demonstrate its effectiveness in
resolving the grating lobes of a sparse array. This enables to achieve high
resolution by deploying a large-aperture array consisting of a small number of
antennas
while avoiding spatial ambiguity. Numerical and experimental examples are used
to illustrate the applicability of our results.
Tea will be provided at 3:30pm.
Wednesday November 23, 2005 at 3:30 PM in SEO 512