West Texas array experiment: Noise and source characterization of short-range infrasound and acoustic signals, along with lab and field evaluation of Intermountain Laboratories infrasound microphones

The term infrasound describes atmospheric sound waves with frequencies below 20 Hz, while acoustics are classified within the audible range of 20 Hz to 20 kHz. Infrasound and acoustic monitoring in the scientific community is hampered by low signal-to-noise ratios and a limited number of studies on regional and short-range noise and source characterization. The JASON Report (2005) suggests the infrasound community focus on more broad-frequency, observational studies within a tactical distance of 10 km. In keeping with that recommendation, this paper presents a study of regional and short-range atmospheric acoustic and infrasonic noise characterization, at a desert site in West Texas, covering a broad frequency range of 0.2 to 100 Hz. To spatially sample the band, a large number of infrasound gauges was needed. A laboratory instrument analysis is presented of the set of low-cost infrasound sensors used in this study, manufactured by Inter-Mountain Laboratories (IML). Analysis includes spectra, transfer functions and coherences to assess the stability and range of the gauges, and complements additional instrument testing by Sandia National Laboratories. The IMLs documented here have been found reliably coherent from 0.1 to 7 Hz without instrument correction. Corrections were built using corresponding time series from the commercially available and more expensive Chaparral infrasound gauge, so that the corrected IML outputs were able to closely mimic the Chaparral output.;Arrays of gauges are needed for atmospheric sound signal processing. Our West Texas experiment consisted of a 1.5 km aperture, 23-gauge infrasound/acoustic array of IMLs, with a compact, 12 m diameter grid-array of rented IMLs at the center. To optimize signal recording, signal-to-noise ratio needs to be quantified with respect to both frequency band and coherence length. The higher-frequency grid array consisted of 25 microphones arranged in a five by five pattern with 3 meter spacing, without spatial wind noise filtering hoses or pipes. The grid was within the distance limits of a single gauge's normal hose array, and data were used to perform a spatial noise correlation study. The highest correlation values were not found in the lower frequencies as anticipated, owing to a lack of sources in the lower range and the uncorrelated nature of wind noise. The highest values, with cross-correlation averages between 0.4 and 0.7 from 3 to 17 m between gauges, were found at night from 10 and 20 Hz due to a continuous local noise source and low wind.;Data from the larger array were used to identify continuous and impulsive signals in the area that comprise the ambient noise field. Ground truth infrasound and acoustic, time and location data were taken for a highway site, a wind farm, and a natural gas compressor. Close-range sound data were taken with a single IML "traveler" gauge. Spectrograms and spectrum peaks were used to identify their source signatures. Two regional location techniques were also tested with data from the large array by using a propane cannon as a controlled, impulsive source. A comparison is presented of the Multiple Signal Classification Algorithm (MUSIC) to a simple, quadratic, circular wavefront algorithm. MUSIC was unable to effectively separate noise and source eignenvalues and eigenvectors due to spatial aliasing of the propane cannon signal and a lack of incoherent noise. Only 33 out of 80 usable shots were located by MUSIC within 100 m. Future work with the algorithm should focus on location of impulsive and continuous signals with development of methods for accurate separation of signal and noise eigenvectors in the presence of coherent noise and possible spatial aliasing. The circular wavefront algorithm performed better with our specific dataset and successfully located 70 out of 80 propane cannon shots within 100 m of the original location, 66 of which were within 20 m. This method has low computation requirements, making it well suited for real-time automated processing and smaller computers. Future research could focus on development of the method for an automated system and statistical impulsive noise filtering for higher accuracy.