Blind deconvolution of sources of opportunity in ocean waveguides using bilinear channel models

We develop a general algorithmic framework for acoustic imaging using sources of opportunity. While these sources (e.g., ships at known locations) emit high-energy signals, we do not in general have knowledge of the precise waveforms (signatures) of these signals. Consequently, 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, we apply a principle component analysis technique 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 red...