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Applied Mathematics Colloquium

Friday, February 1, 11:30 am
Cullimore Lecture Hall II
New Jersey Institute of Technology

Imaging in Clutter

George Papanicolaou

Department of Mathematics

Stanford University

Stanford, CA

Abstract

I will review briefly the basic ideas in array imaging and then introduce a two-step algorithm for optimal illumination and subspace selection with adaptive coherent interferometry in order to image clusters of small scatterers in clutter, that is, in randomly inhomogeneous environment. Adaptive coherent interferometry is a way to image with array data that is robust in clutter because it uses correlations of the data. I will be introduce and discuss it in some detail. In the two-step algorithm, the first step uses the singular value decomposition of the array response matrix to image the scatterers in a selective manner, one at a time. The second step is designed to improve the image of each scatterer using an optimal illumination from the array. I will show results from numerical simulations that illustrate the performance of the algorithm. Applications include ultrasonic non-destructive testing, sonar, broadband radar, etc.