Eliza of New Jersey Institute of Technology

Localizing a sound source in the ocean and being able to characterize the oceanic environment is an inverse problem of critical importance in antisubmarine warfare.  Matched-field inversion (MFI) is a method frequently used to address this highly complex challenge.  It entails the maximization of a correlation measure between received data at an array of hydrophones and replica fields calculated with a sound propagation model for a set of values for environmental parameters as well as source location. The values that produce the maximum correlation form the estimates of the unknown parameters.  In this presentation we first discuss the mechanics of MFI.  We then look at the potential of solving the inverse problem at an array of hydrophones we wish we had, not the one that is actually deployed.  Towards this goal, we generate via Gaussian Process regression virtual arrays and compute the field at the hydrophones therein; this enables dense sampling of the water column by introducing the concept of virtual receivers.  MFI is a highly successful approach to inverse problems. There are, however, situations where the implementation is computationally challenging. Alternatives for such situations will be discussed.

Biography:

Eliza (Z.-H.) Michalopoulou received the Diploma in Electrical
Engineering from the National Technical University of Athens, Athens,
Greece, and the M.S. and Ph.D. degrees in Electrical Engineering from
Duke University, Durham, NC. Currently, she is a Professor of
Mathematical Sciences at the New Jersey Institute of Technology,
Newark, NJ. Her research interests include ocean acoustics, Bayesian
modeling and uncertainty quantification, inverse problems, undersea
signal processing, and machine learning. Dr. Michalopoulou is a Fellow
of the Acoustical Society of America, a Senior Member of IEEE, a
member of SIAM, and a member of the Pi Mu Epsilon Honor Society.

Email:

Address:Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, United States, 07102