Adaptive Noise Reduction Techniques for Airborne Acoustic Sensors

Abstract

Ground and marine based acoustic arrays are currently employed in a variety of military and civilian applications for the purpose of locating and identifying sources of interest. An airborne acoustic array could perform an identical role, while providing the ability to cover a larger area and pursue a target. In order to implement such a system, steps must be taken to attenuate environmental noise that interferes with the signal of interest. In this thesis, we discuss the noise sources present in an airborne environment, present currently available methods for mitigation of these sources, and propose the use of adaptive noise cancellation techniques for removal of unwanted wind and engine noise. The least mean squares, affine projection, and extended recursive least squares algorithms are tested on recordings made aboard an airplane in-flight, and the results are presented. The algorithms provide upwards of 37dB of noise cancellation, and are able to filter the noise from a chirp with a signal to noise ratio of -20db with minimal mean square error. The experiment demonstrates that adaptive noise cancellation techniques are an effective method of suppressing unwanted acoustic noise in an airborne environment, but due to the complexity of the environment more sophisticated algorithms may be warranted.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2012
Accession Number
ADA573518

Entities

People

  • Ryan M. Fuller

Organizations

  • Wright State University

Tags

Communities of Interest

  • Air Platforms
  • Engineered Resilient Systems
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acoustic Arrays
  • Acoustic Detectors
  • Acoustics
  • Aircrafts
  • Airframes
  • Airplanes
  • Atmospheric Attenuation
  • Attenuators
  • Detection
  • Detectors
  • Engine Noise
  • Fixed Wing Aircraft
  • Fluid Flow
  • Internal Combustion Engines
  • Noise Reduction
  • Signal Processing
  • Warning Systems

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Radar Systems Engineering.
  • Systems Analysis and Design