Shallow water acoustic response and platform motion modeling via a hierarchical Gaussian mixture model.
A hierarchical Gaussian mixture model is proposed to characterize shallow water acoustic response functions that are time-varying and sparse. The mixture model is based on the assumption that acoustic paths can be partitioned into two sets. The first is a relatively coherent set of arrivals that on average exhibit Doppler spreading about a mean Doppler and the remaining set is of multiple surface scattered paths that exhibit a spectrally flat Doppler. The hierarchy establishes constraints on the parameters of each of these Gaussian models such that coherent components of the response are both sparse and in the ensemble obey the Doppler spread profile. This is accomplished with a Bernoulli model that indicates the ensonification state of each element in the bi-frequency representation of the acoustic response function. Estimators of the time-varying acoustic response for the full duration of a broadband transmission are developed and employed to compensate for the shared time-varying dilation process among the coherent arrivals. The approach ameliorates response coherence degradation and can be employed to enhance coherent multi-path combining and is a useful alternative to time recursive estimation. The model is tested with acoustic communication recordings taken in shallow water at low signal-to-noise ratios.
University of Massachusetts Dartmouth, College of Engineering, 285 Old Westport Road, North Dartmouth, Massachusetts 02747, USA.
Paul J
PJ
Gendron