Improvements to infrasonic detection capabilities through application of a generalized least squares beamformer

A common challenge in seismoacoustic research and analysis is detection of low signal-to-noise ratio (SNR) signals in a variable and often coherent background. Previously, the application of an adaptive F-detector to infrasonic data has successfully reduced false detection rates attributed to coherent noise across array elements; however, the detector is applied post-processing after analysis using a standard (Bartlett) beamformer, which raises the detection threshold and can lead to missed detections. Application of a generalized least squares (GLS) beamformer can enhance processing of transient infrasonic signals, particularly in the presence of correlated noise, by adaptively accounting for the background noise characteristics. The GLS beamformer enhancement leads to improved capabilities for accurately detecting low amplitude infrasonic events of interest that would not normally produce a sufficiently high F-statistic to be declared a detection. A statistical analysis of GLS beamformer performance in ...