Statistical Discrimination. Higher Mode Detection Studies

The report presents results of applying a maximum entropy power spectrum analysis technique to detect higher order mode surface waves. The algorithm used partitioned each seismogram into time gates representing average group velocities, and spectral analysis was used to determine the periods of the...

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Bibliographic Details
Main Author: Swindell, William H
Other Authors: TEXAS INSTRUMENTS INC DALLAS SERVICES GROUP
Format: Text
Language:English
Published: 1970
Subjects:
Seismology
Seismic Detection and Detectors
*SEISMOLOGICAL STATIONS
*UNDERGROUND EXPLOSIONS
ALASKA
ALEUTIAN ISLANDS
CALIFORNIA
CHINA
DETECTION
EARTHQUAKES
ELECTROMAGNETIC WAVE FILTERS
EUROPE
JAPAN
MONTANA
NOISE
NUCLEAR EXPLOSIONS
POWER SPECTRA
RAYLEIGH WAVES
SEISMOMETERS
SIGNAL TO NOISE RATIO
SPECTRUM SIGNATURES
TIME SERIES ANALYSIS
*LARGE APERTURE SEISMIC ARRAY
*LASA(LARGE APERTURE SEISMIC ARRAY)
LONG PERIOD SEISMOMETERS
SPECTRUM ANALYSIS
VELA UNIFORM
Alaska
Aleutian Islands
Online Access:http://www.dtic.mil/docs/citations/AD0880494
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=AD0880494
Description
Summary:The report presents results of applying a maximum entropy power spectrum analysis technique to detect higher order mode surface waves. The algorithm used partitioned each seismogram into time gates representing average group velocities, and spectral analysis was used to determine the periods of the data in the gates. The technique was tested successfully on artificial seismograms containing the Rayleigh and three higher modes of surface waves, with and without additive noise. Maximum entropy power spectrum analysis techniques were applied to an ensemble of 29 long-period seismograms obtained from LASA beams. The long-period seismograms were of both continental and continental-oceanic paths. While several instances of possible higher mode waves were revealed by the analysis, no consistency was found in the occurrence of these modes. Major conclusions were that ME spectrum analysis provides finer details in seismogram spectra than are otherwise available and that it provides an effective method for computing group-velocity frequency curves. See also Report no. 2, AD0871116.

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