Model-based signal enhancement for the Hudson Canyon experiment

Journal Article · Sat Dec 31 04:00:00 EST 1994 · Journal of Computational Acoustics

DOI:https://doi.org/10.1142/S0218396X9400021X· OSTI ID:147903

Candy, J V ^[1]; Sullivan, E J ^[2]

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1. Univ. of California, Livermore, CA (United States). Lawrence Livermore National Lab.
2. Naval Undersea Warfare Center, Newport, RI (United States)

The detection, localization, and classification of acoustic sources (targets) has long been a problem, especially now due to the current advances in submarine construction technology. The advent of more and more diesel-powered vessels makes the detection problem more formidable. It has recently been recognized that the incorporation of a mathematical model that accurately represents the phenomenology under investigation can vastly improve the performance of any processor, that is, as long as the model is accurate. Model-based signal processing is a well-defined methodology enabling the inclusion of environmental (propagation) models, measurement (sensor arrays) models, and noise (shipping, measurement) models into a sophisticated processing algorithm. Here the authors investigate the design of a space-varying, nonstationary, model-based processor (MBP) for the Hudson Canyon experiment. In this shallow water application, a state space representation of the normal mode propagation model is used. The processor is designed such that it allows in situ recursive estimation of the both the pressure field and modal functions. It is shown that the MBP can be effectively utilized to ``validate`` the performance of the model on noisy ocean acoustic data. In fact, a set of processors is designed, one for each source range, and the results are reasonable, implying that the propagation model with measured parameters adequately represents the data. 34 refs., 4 figs., 2 tabs.

• Sponsoring Organization: USDOE
• DOE Contract Number: W-7405-ENG-48
• OSTI ID: 147903
• Journal Information: Journal of Computational Acoustics, Journal Name: Journal of Computational Acoustics Journal Issue: 3 Vol. 2; ISSN JCOAEJ
• Country of Publication: United States
• Language: English

Related Subjects

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEFENSE
ACOUSTIC DETECTION
ATLANTIC OCEAN
COASTAL WATERS
DATA ANALYSIS
MATHEMATICAL MODELS
NEW JERSEY
NUMERICAL DATA
PRESSURE MEASUREMENT
SIGNAL CONDITIONING
SIGNAL-TO-NOISE RATIO
SONAR
SOUND WAVES
SUBMARINES
WAVE PROPAGATION