Acoustic Background Noise Variation in Air Force Platforms and Its Effect on Noise Removal Algorithms

Abstract

In this study of short-term noise variation in Air Force platforms, we followed two avenues of investigation. First, we applied quantitative measures of variation to individual noise recordings, and compared the results across various aircraft. Some measures used were simple descriptive statistics, but we also measured attenuation obtained by spectral restoration (spectral subtraction), applied to the noise signal alone. The noise attenuation obtained for real aircraft environments was in most cases about the same as predicted theoretically for white Gaussian noise, but in some instances was considerably higher, especially in the presence of propeller noise. Second, we applied the nonparametric Mann-Whitney statistic to test the stationarity of power spectrum estimates on time scales of 200 to 800 ms. There was little or no evidence of nonstationarity in large jet or turboprop aircraft. In fighter aircraft and helicopters, there was some evidence of nonstationarity confined to more or less narrow frequency ranges. The nonstationarity found did not appear to limit the performance of special restoration algorithms. The noise recordings used were taken from the RADC/EEV database of field recordings made in the E-3A, E-4B, EC- 135, E-130, P-3C, F-15, F-16, F-4, A-10, HH-53 and Tornado aircraft.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1991
Accession Number
ADA238279

Entities

People

  • Philip A. Lafollette

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Aircraft Equipment
  • Aircrafts
  • Airframes
  • Attack Aircraft
  • Data Science
  • Databases
  • Fighter Aircraft
  • Human Factors Engineering
  • Information Processing
  • Information Science
  • Random Variables
  • Stationary Processes
  • Statistical Algorithms
  • Surveys
  • Turbines
  • Turboprop Engines

Readers

  • Acoustics.
  • Regression Analysis.
  • Theoretical Analysis.