Modeling and Processing for Vector Sensors

Abstract

LONG-TERM GOALS. Using recently developed sensor technology, the long-term goals are to understand how pressure and particle velocity interact and propagate in the ocean waveguide, and to develop ideas for future naval systems that benefit from this technology. OBJECTIVES. The objectives of this work are: to develop models and processing techniques for acoustic vector sensors, to collect data at sea during the Makai Experiment (at Kauai's PMRF in September 05), and to demonstrate processing capabilities that exploit the unique characteristics of vector sensors. APPROACH We have collected data at-sea during the Makai experiment in September 2005, using a 5-element array of Wilcoxon TV-001 vector sensors, borrowed from Jerry Tarasek at NSWC-Carderock. Our approach for modeling vector sensors will be to initially use normal modes for low frequencies and Gaussian beams for mid to high frequencies, basically piggy-backing upon existing models to calculate pressure at a set of points from which the various pressure derivatives can be calculated (i.e. a finite difference approximation). We plan to compare our models with the data we have recorded at sea. In addition to using the collected data to validate our models, we plan to assess improvements afforded by vector sensors in broadband model-based tracking, acoustic communications, and using ambient noise to image the seafloor sediment layers.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2006
Accession Number
ADA630885

Entities

People

  • Paul Hursky

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Acoustic Communications
  • Ambient Noise
  • Arrays
  • Calibration
  • Detectors
  • Frequency
  • Frequency Bands
  • Frequency Domain
  • Measurement
  • Noise
  • Optical Lattices
  • Particles
  • Physical Sciences
  • Seabed
  • Test Facilities
  • Towed Arrays
  • Unmanned Vehicles

Readers

  • Computer Vision.
  • Oceanography.
  • Systems Analysis and Design