Accession Number:

ADA571511

Title:

Impulse Noise Bearing and Amplitude Measurement and Analysis System (BAMAS)

Descriptive Note:

Final rept. 2005-2010

Corporate Author:

APPLIED PHYSICAL SCIENCES CORP GROTON CT

Report Date:

2010-03-01

Pagination or Media Count:

49.0

Abstract:

The BAMAS project addresses SERDP CPSON 05-04 for improving the measurement, analysis, archiving and reporting of impulsive acoustic noise emanating from within a military installation. Impulsive noise events that cause public alarm are loud, high signal-to-noise ratio, short-duration acoustic pulses from explosions, impacts, large caliber artillery fire, and sometimes sonic booms. Impulsive noise monitoring systems play a critical role in the relationship between test and training managers, environmental safetycompliance officers and the general public residing adjacent to military installations. Noise monitoring systems are needed for quantifying the magnitude and time of impulsive noise events, to ensure compliance and to provide an archival record of noise emanating from the installation. There are several commercial systems but they report excessive false positives as a result of windborne noise and distant non-military acoustic events. This can bias noise statistics to the point where meaningful assessment of the acoustic sound levels from a site is not possible. APS, in collaboration with the University of Pittsburgh, have developed an improved noise monitoring system, called BAMAS Bearing and Amplitude Measurement and Analysis System, for mitigating windborne and other sources of non-military noise. This system includes a collection of remote sensors capable of detection, localization, and classification. The classifier was developed by the University of Pittsburgh under separate SERDP programs, SI-1436 and SI-1585, and integrated by APS into the BAMAS software. A prototype is installed at an active military base where it has been reporting and archiving impulse noise since October of 2009. In just 2 months, the BAMAS system has archived over 3000 events of which none were incorrectly classified as blast noise. The BAMAS algorithm was found to reject 99.5 of the non-blast noise specifically wind recorded while retaining 97.7 of all blast noise.

Subject Categories:

  • Acoustic Detection and Detectors
  • Acoustics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE