skip to main content

SciTech ConnectSciTech Connect

This content will become publicly available on April 14, 2017

Title: Broadband Processing in a Noisy Shallow Ocean Environment: A Particle Filtering Approach

Here we report that when a broadband source propagates sound in a shallow ocean the received data can become quite complicated due to temperature-related sound-speed variations and therefore a highly dispersive environment. Noise and uncertainties disrupt this already chaotic environment even further because disturbances propagate through the same inherent acoustic channel. The broadband (signal) estimation/detection problem can be decomposed into a set of narrowband solutions that are processed separately and then combined to achieve more enhancement of signal levels than that available from a single frequency, thereby allowing more information to be extracted leading to a more reliable source detection. A Bayesian solution to the broadband modal function tracking, pressure-field enhancement, and source detection problem is developed that leads to nonparametric estimates of desired posterior distributions enabling the estimation of useful statistics and an improved processor/detector. In conclusion, to investigate the processor capabilities, we synthesize an ensemble of noisy, broadband, shallow-ocean measurements to evaluate its overall performance using an information theoretical metric for the preprocessor and the receiver operating characteristic curve for the detector.
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
OSTI Identifier:
Report Number(s):
Journal ID: ISSN 0364-9059
Grant/Contract Number:
Accepted Manuscript
Journal Name:
IEEE Journal of Oceanic Engineering
Additional Journal Information:
Journal Issue: 99; Journal ID: ISSN 0364-9059
Research Org:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA
Sponsoring Org:
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; 47 OTHER INSTRUMENTATION littoral region; normal-modes; broadband Bayesian processor; sequential Monte Carlo; particle filter; performance metrics; information theory; Kullback-Leibler divergence; sequential detection