October, 2002 Infrasonic Signal Detection Using The Hough Transform D. J. Brown, B.L.N. Kennett, C. Tarlowski Research School of Earth Sciences, Australian National University, Canberra, 0200, Australia

October, 2002 Overview Motivation The Hough Transform Three-Dimensional array processing ‘INFER’ detector design Examples Summary

October, 2002 Motivation Based on the premise that signal duration may be a significant discriminant –a signal with an extended duration is at least indicative that ‘something’ is happening ‘somewhere’ Infrasonic detection algorithms with an ‘instantaneous’ detection philosophy will likely never operate at sufficiently low thresholds to detect all significant signals –e.g., a pure Fstat-detector cannot reasonably operate with the detection threshold set much below 6. –traditionally a threshold is set and signal duration is defined by how long the signal stays above threshold. It remains to obtain a correct measure of signal duration

October, 2002 Motivation Etna Volcano [I26DE, Freyung, Germany] Acoustic signal from Etna volcano recorded at I26DE –a significant signal Distinct lack of –correlation –amplitude Average Fstat around 4.3 Only two integration intervals with Fstats > 6 –Using a pure Fstat detector, measuring signal duration based on above-threshold-time-durations will yield very short signal durations Signal presence is obvious to the human eye by the dominant azimuth and trace velocity

October, 2002 Motivation STS-96 [DLIAR, Los Alamos] Acoustic signal from shuttle launch STS-96 recorded at DLIAR, Los Alamos –a significant signal Distinct lack of – correlation –amplitude Average Fstat around 4.3 Maximum Fstat ~ 6 –Using a pure Fstat detector, determining signal duration based on above threshold time durations will yield very short signal durations Signal presence is obvious to the human eye due to the dominant azimuth and trace velocity

October, 2002 Motivation Need to design a detection strategy based on the persistence of the measured backazimuth during the passage of the signal –Certain tools in Pattern Recognition theory may be useful Envisage a detection algorithm that –has two parts: parameter extraction over short time intervals. seeks regions of persistent backazimuth, regardless of any threshold parameter. –Thresholding since the short duration industrial-type signals are more prevalent than the longer duration signals of interest, and generally not as important, define a set of signal duration thresholds that may be frequency band- dependent. –Uses 3D array geometry

October, 2002 The Hough Transform method for doing pattern recognition extracts parametric curve information from binary pixelated data in the presence of noise consider binary image data: apply the transformation: –maps points in S into lines in parameter space, P –all points on the same line in S have the same intersection point in P Pairs of points (x i y i ), (x j,y j ) in S are mapped to the point (  ) in P where Problem of detecting spatially extended lines becomes one of finding a local maximum

October, 2002 The Hough Transform Image Space, S Parameter Space, P Hough Transform

October, 2002 The Hough Transform Image Space, S Parameter Space, P Hough Transform STS-96 [DLIAR, Los Alamos]

October, 2002 INFER Detector Design (I) Detection philosophy: measure accurately: signal duration arrival time backazimuth one single detection per phase relieves the burden on down-stream processing does away with the infrasonic ‘coda’ phase

October, 2002 INFER Detector Design (I) Two stage detection process signal parameter estimation in 3D delay-and-sum correlation (in use) global minimization of the mis-match between theoretical and stacked trace beam powers (presently testing -see Poster) maximum beam-power by contracting grid (presently testing -see Poster) Signal detection via the Hough Transform to prevent spurious associations between pairs of points, define a maximum time separation that can exist between any pair of points. define an accumulator mesh whose granularity is commensurate with the uncertainty in the measured azimuth. keep track of the features of all integration intervals that contributed to any one accumulator cell..

October, 2002 INFER Detector Design (II) Phase Identification may need to decide phase during source location Basic nomenclature: Thresholding for detection signal duration dependent thresholds Fstat STA/LTA –take the STA interval to be the entire integration interval –take the LTA interval to be the entire time-block requested –various norms: L1, L2 integrated power signal duration

October, 2002 INFER Detector Design (III) Thresholds –signal duration dependent –processing frequency-band dependent

October, D Array Processing  Jin Wang (1999) shows that significant vertical sensor separations can strongly influence: –measured backazimuth –magnitude slowness –beam power We extend slowness plane to 3rd dimension: (s x,s y,s z ) Create a mesh in the 3D half-space Consider only those points that lie in an  thick dome centered on the acoustic slowness. [Recently] Use  = 0 ! –Use Cs determined by Value of Temperature recorded at the array climatological model Constant = 330 m/s |s| = 1/C s

October, 2002 Results Shuttle launch signal -DLIAR

October, 2002 Results Gas pipeline explosion -DLIAR

October, 2002 Results

October, 2002 Results

October, 2002 Results

October, 2002 Results Seattle Earthquake -I10CA

October, 2002 Results Acapulco Bolide -I59US

October, 2002 Results Etna volcano -I26DE

October, 2002 Summary Detecting infrasound signals from IMS array data by seeking regions of constant backazimuth seems to be a robust procedure –backazimuth can be accurately determined –signal duration can be accurately inferred The Hough Transform can be used quite effectively to look for regions of constant backazimuth –signals with moderate to small Fstat can be detected An automatic signal detection algorithm called INFER based on the Hough Transform has been created –uses 3D array geometry –uses correlator to do feature extraction testing other procedures –incorporates basic phase id –interfaces dynamically with the CSS database tables