Infrasonic Signal Detection Usin by pengxiang

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									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
                                           •   Acoustic signal from Etna volcano
Motivation                                     recorded at I26DE
Etna Volcano                                    – 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
               [I26DE, Freyung, Germany]
                                      •   Acoustic signal from shuttle launch
   Motivation                             STS-96 recorded at DLIAR, Los
                                          Alamos
STS-96
                                           – 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

                [DLIAR, Los Alamos]

                                                             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:           S  xi , yi  where i  1,, N
 •   apply the transformation:             m  xit  yi
      – 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 (xiyi), (xj,yj) in S are mapped to the point (m,t)in P where
                           y j  yi 
              m  yi  xi 
                          
                                     
                                     
                           x j  xi 
                        y j  yi 
              t                 
                       x x 
                        j       i 
 •   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



                   dy / dx  2




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

STS-96


                                     Hough Transform




               [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:
            phase                     description                           |s| limits
          Iw         Tropospheric-wind ducted phase                           < 340
          Is         Stratospheric ducted phase                             340-380
          It         Thermospheric ducted phase                                > 380


• 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, 2002
    3D Array Processing
•   Jin Wang (1999) shows that significant
    vertical sensor separations can strongly
    influence:
     – measured backazimuth
     – magnitude slowness
     – beam power                                 e
•   We extend slowness plane to 3rd
    dimension: (sx,sy,sz)
•   Create a mesh in the 3D half-space
                                                      |s| = 1/Cs
•   Consider only those points that lie in an
    e thick dome centered on the acoustic
    slowness.
•   [Recently] Use e = 0 !
     – Use Cs determined by
         • Value of Temperature recorded at the
           array
         • climatological model                                    October, 2002
         • Constant = 330 m/s
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    October, 2002

								
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