Computationally robust and noise resistant numerical detector for the detection of atmospheric infrasound.

This work reports on a performance study of two numerical detectors that are particularly useful for infrasound arrays operating under windy conditions. The sum of squares of variance ratios (SSVR1)-proposed for detecting signals with frequency ranging from 1 to 10 Hz-is computed by taking the ratio of the squared sum of eigenvalues to the square of largest eigenvalue of the covariance matrix of the power spectrum. For signals with lower frequency between 0.015 and 0.1 Hz, SSVR2 is developed to reduce the detector's sensitivity to noise. The detectors' performances are graphically compared against the current method, the mean of cross correlation maxima (MCCM), using the receiver operating characteristics curves and three types of atmospheric infrasound, corrupted by Gaussian and Pink noise. The MCCM and SSVR2 detectors were also used to detect microbaroms from the 24 h-long infrasound data. It was found that the two detectors outperform the MCCM detector in both sensitivity and computational efficiency. For mine blasts corrupted by Pink noise (signal-to-noise ratio = -7 dB), the MCCM and SSVR1 detectors yield 62 and 88 % true positives when accepting 20% false positives. For an eight-sensor array, the speed gain is approximately eleven-fold for a 50 s long signal.

Explosion localization via infrasound.

Two acoustic source localization techniques were applied to infrasonic data and their relative performance was assessed. The standard approach for low-frequency localization uses an ensemble of small arrays to separately estimate far-field source bearings, resulting in a solution from the various back azimuths. This method was compared to one developed by the authors that treats the smaller subarrays as a single, meta-array. In numerical simulation and a field experiment, the latter technique was found to provide improved localization precision everywhere in the vicinity of a 3-km-aperture meta-array, often by an order of magnitude.

Uncertainties associated with parameter estimation in atmospheric infrasound arrays.

This study describes a method for determining the statistical confidence in estimates of direction-of-arrival and trace velocity stemming from signals present in atmospheric infrasound data. It is assumed that the signal source is far enough removed from the infrasound sensor array that a plane-wave approximation holds, and that multipath and multiple source effects are not present. Propagation path and medium inhomogeneities are assumed not to be known at the time of signal detection, but the ensemble of time delays of signal arrivals between array sensor pairs is estimable and corrupted by uncorrelated Gaussian noise. The method results in a set of practical uncertainties that lend themselves to a geometric interpretation. Although quite general, this method is intended for use by analysts interpreting data from atmospheric acoustic arrays, or those interested in designing and deploying them. The method is applied to infrasound arrays typical of those deployed as a part of the International Monitoring System of the Comprehensive Nuclear-Test-Ban Treaty Organization.