Blind deconvolution of sources of opportunity in ocean waveguides using bilinear channel models
Abstract
A general blind deconvolution algorithmic framework is developed for sources of opportunity (e.g., ships at known locations) in an ocean waveguide. Here, both channel impulse responses (CIRs) and unknown source signals need to be simultaneously estimated from only the recorded signals on a receiver array using blind deconvolution, which is generally an ill-posed problem without any a priori information or additional assumptions about the underlying structure of the CIRs. By exploiting the typical ray-like arrival-time structure of the CIRs between a surface source and the elements of a vertical line array (VLA) in ocean waveguides, a principle component analysis technique is applied to build a bilinear parametric model linking the amplitudes and arrival-times of the CIRs across all channels for a variety of admissible ocean environments. The bilinear channel representation further reduces the dimension of the channel parametric model compared to linear models. A truncated power interaction deconvolution algorithm is then developed by applying the bilinear channel model to the traditional subspace deconvolution method. Numerical and experimental results demonstrate the robustness of this blind deconvolution methodology.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 01, 2020
- Source ID
- 10.1121/10.0001975
Entities
People
- Justin Romberg
- Karim G. Sabra
- Kiryung Lee
- Nicholas Durofchalk
- Ning Tian
Organizations
- Georgia Tech
- National Science Foundation
- Office of Naval Research
- Ohio State University