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Title: Ocean acoustic signal processing: A model-based approach

Abstract

A model-based approach is proposed to solve the ocean acoustic signal processing problem that is based on a state-space representation of the normal-mode propagation model. It is shown that this representation can be utilized to spatially propagate both modal (depth) and range functions given the basic parameters (wave numbers, etc.) developed from the solution of the associated boundary value problem. This model is then generalized to the stochastic case where an approximate Gauss--Markov model evolves. The Gauss--Markov representation, in principle, allows the inclusion of stochastic phenomena such as noise and modeling errors in a consistent manner. Based on this framework, investigations are made of model-based solutions to the signal enhancement, detection and related parameter estimation problems. In particular, a modal/pressure field processor is designed that allows {ital in} {ital situ} recursive estimation of the sound velocity profile. Finally, it is shown that the associated residual or so-called innovation sequence that ensues from the recursive nature of this formulation can be employed to monitor the model's fit to the data and also form the basis of a sequential detector.

Authors:
 [1];  [2]
  1. University of California, Lawrence Livermore National Laboratory, P.O. Box 5504, L-495, Livermore, California 94550 (United States)
  2. Naval Underseas Warfare Center, NUWC Code 103, Newport, Rhode Island 02841 (United States)
Publication Date:
OSTI Identifier:
6950858
Resource Type:
Journal Article
Journal Name:
Journal of the Acoustical Society of America; (United States)
Additional Journal Information:
Journal Volume: 92:6; Journal ID: ISSN 0001-4966
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; SOUND WAVES; ACOUSTIC DETECTION; BOUNDARY-VALUE PROBLEMS; DEPTH; GAUSSIAN PROCESSES; OCEANOGRAPHY; RANGE; ACOUSTIC MEASUREMENTS; CHARGED PARTICLE DETECTION; DETECTION; DIMENSIONS; RADIATION DETECTION; 661300* - Other Aspects of Physical Science- (1992-)

Citation Formats

Candy, J V, and Sullivan, E J. Ocean acoustic signal processing: A model-based approach. United States: N. p., 1992. Web. doi:10.1121/1.404168.
Candy, J V, & Sullivan, E J. Ocean acoustic signal processing: A model-based approach. United States. https://doi.org/10.1121/1.404168
Candy, J V, and Sullivan, E J. 1992. "Ocean acoustic signal processing: A model-based approach". United States. https://doi.org/10.1121/1.404168.
@article{osti_6950858,
title = {Ocean acoustic signal processing: A model-based approach},
author = {Candy, J V and Sullivan, E J},
abstractNote = {A model-based approach is proposed to solve the ocean acoustic signal processing problem that is based on a state-space representation of the normal-mode propagation model. It is shown that this representation can be utilized to spatially propagate both modal (depth) and range functions given the basic parameters (wave numbers, etc.) developed from the solution of the associated boundary value problem. This model is then generalized to the stochastic case where an approximate Gauss--Markov model evolves. The Gauss--Markov representation, in principle, allows the inclusion of stochastic phenomena such as noise and modeling errors in a consistent manner. Based on this framework, investigations are made of model-based solutions to the signal enhancement, detection and related parameter estimation problems. In particular, a modal/pressure field processor is designed that allows {ital in} {ital situ} recursive estimation of the sound velocity profile. Finally, it is shown that the associated residual or so-called innovation sequence that ensues from the recursive nature of this formulation can be employed to monitor the model's fit to the data and also form the basis of a sequential detector.},
doi = {10.1121/1.404168},
url = {https://www.osti.gov/biblio/6950858}, journal = {Journal of the Acoustical Society of America; (United States)},
issn = {0001-4966},
number = ,
volume = 92:6,
place = {United States},
year = {Tue Dec 01 00:00:00 EST 1992},
month = {Tue Dec 01 00:00:00 EST 1992}
}