The local infrasound environment in Alaska is rich in both natural and human-generated sources. Identifying the source and localizing it is a challenge with many different applications. The Infrasound group at UAF has operated arrays in Alaska and Antarctica for several years. The primary arrays are comprised of eight microphones arranged to obtain wide-band operation with no spatial aliasing over the frequency band of interest. These arrays are operated and maintained by the UAF group as part of the International Monitoring System (IMS) of the United Nations Comprehensive Nuclear Test-Ban Treaty Office (CTBTO). A second array of four microphones is operated by the UAF group as a research array. The group has used this array to test methods of wind-noise reduction, microphone performance and array performance under varying array geometries. As part of the process of identifying infrasound signal sources a prototype locator algorithm was developed that allows estimation of the range to the signal source for locations of the signals source of up to 10 to 15 times the array diameter. The locator algorithm has been used extensively in cases where signal-to-noise levels are high and it appears to be robust. Investigators will continue to study the method and investigate its behavior under a range of signal-to-noise conditions, as well as develop an estimator of the variance in the estimates of range and azimuth.
The description and classification of signal sources will improve the ability to discriminate against known natural and man-made sources in signal detection operations. The development of an algorithm to estimate source range to accompany the traditional azimuth estimates will also benefit the general area of source localization using acoustic methods. This algorithm should be transferable to any detection program using arrays of sensors.
PI: John Olson Award Number: 0433392 The goals of this research project were: 1) to review the infrasound data in the UAF database to identify significant natural and man-made events, 2) to develop and test the UAF location algorithm. Over the span of this award a significant effort was applied to each of the goals with important outcomes. The UAF database contains data from the CTBT infrasound array from two arrays. The first, designated as I53, is located in a wooded area of the UAF campus in Fairbanks, Alaska. The second, designated as I55, is located near McMurdo Station, Antarctica. The arrays have been in operation nearly continuously since 2002 providing data from the eight microphones that make up each array. A detection scheme was devised based upon the use of two detection algorithms. The first is a correlation detector based upon the mean of the cross-correlation maxima (MCCM) and the second is based upon the F-statistic (FSTAT). Infrasound data from each 24-hour day are segmented into three frequency bands, low (0.01 – 0.1 Hz), microbarom (0.1 – 0.7 Hz) and high (0.7 – 10 Hz). A sliding analysis window moves across the data from each band producing estimates of the MCCM, FSTAT as well as the least-squares estimates of arrival azimuth and trace speed. Probability distribution functions are devised from the detector statistics and a detection threshold is set. Values of the detectors that rise above the threshold are tagged as possible events. All of the information produced by this process is archived electronically and in graphic form for review. We have found that there can be as many as 10,000 events per year in the Fairbanks array. In addition to the detection summary plots we also produce plots of signal azimuth versus trace velocity in a polar diagram covering each month of data. Using these tools we are able to identify several consistent sources of infrasound signals in the local region. These include the explosions from a local gold mine, aircraft using the Fairbanks International Airport, and a host of other man-made sources. In addition, we have detected signals from landslides and avalanches in the mountain ranges to the south of Fairbanks. The dominant event of the decade was the infrasound associated with the great Denali earthquake of 2002. We were able to trace the location of the epicenter as it moved eastward along the Alaska Range. The acoustic signals were attributed to the lateral motion of the mountain range as the epicenter moved past.(1) A new discovery was made in the analysis of long-period waves associated with auroral activity.(2) This topic is now the subject of a PhD thesis. At the McMurdo site we regularly observe the eruptions of Mt Erebus, located some 30km from our array. In addition, auroral signals, microbaroms and mountain-associated waves are observed frequently at this quiet southern site. These data were also the source of a PhD dissertation investigating the nature of mountain-associated waves.(3) The second goal of this project was to continue the development of the UAF source location algorithm. This algorithm was developed by our group and, after extensive testing and development, has received a patent.(4) The basis of the algorithm is the use of the time-of-arrival of a signal wave front at each sensor in an array. With this information the kinematic equations of motion can be solved to identify a unique source location. We have carried out extensive simulations and a complete field test to validate the results.(5) The field tests were conducted at Fort Greely, Alaska using three small arrays of microphones spaced approximately 3km from each other. Army personnel set of a large number of explosions at random locations in and near the area where the arrays were located. The resulting data were analyzed using traditional back-azimuth location algorithms and with the UAF Locator algorithm. It was found that the UAF algorithm reduced the uncertainty in locations by about an order of magnitude in each case. Back-azimuth estimates generally showed uncertainties near 100 meters while the UAF locator uncertainties were approximately 10 meters. References: (1) Olson, J. V., C. R. Wilson and R. Hansen, Infrasound associated with the 2002 Denali fault earthquake, Geophys. Res. Lett., V30, 2195, 2003. (2) Wilson, C. R. and J. V. Olson, Auroral infrasound and local geomagnetic disturbances at I53US, Inframatics (on line at www.inframatics.org), September 2008. (3) Lee, D.-C., Neural network approach to classification of infrasound signals, PhD Thesis, University of Alaska Fairbanks, August 2008. (4) Arnoult, K., C. A. L. Szuberla and J. V. Olson, Method and system for conducting near-field source location, US Patent #7746225, 30 November 2005. (5) Szuberla, Curt A. L., John V. Olson and Kenneth M. Arnoult, Explosion location via infrasound, JASA Express Letters (DOI: 10.1121/1.3216742), 24 September 2009.
