Broadband Processing in a Noisy Shallow Ocean Environment: A Particle Filtering Approach
Journal Article
·
· IEEE Journal of Oceanic Engineering
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
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.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC52-07NA27344
- OSTI ID:
- 1262184
- Report Number(s):
- LLNL-JRNL--676434
- Journal Information:
- IEEE Journal of Oceanic Engineering, Journal Name: IEEE Journal of Oceanic Engineering Journal Issue: 99; ISSN 0364-9059
- Country of Publication:
- United States
- Language:
- English
Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor
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