A Technique for Automatic Classification of Meteor Trails and Other Propagation Mechanisms for the Air Force High Latitude Meteor Burst Test Bed.

This report describes a rule-driven artificial intelligence technique for automating the identification of propagation mechanisms and classification of meteor trail types on the USAF high latitude meteor burst test bed. The procedure reduces the time required to process data from one month of test b...

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Bibliographic Details
Main Authors: Weitzen,Jay A, Tolman,Sylvia
Other Authors: SIGNATRON INC LEXINGTON MA
Format: Text
Language:English
Published: 1986
Subjects:
Radiofrequency Wave Propagation
Radio Communications
*METEORS
*RADIO TRANSMISSION
DATA BASES
DENSITY
TEST BEDS
AUTOMATION
SIGNAL TO NOISE RATIO
CONTINUOUS WAVES
ELECTROMAGNETIC WAVE PROPAGATION
IDENTIFICATION
DATA REDUCTION
CLASSIFICATION
ARTIFICIAL INTELLIGENCE
HIGH LATITUDES
GREENLAND
IONOSPHERIC PROPAGATION
Meteor scatter propagation identification
Meteor trail density
meteor burst communications
PE62702F
WURADC46001666
Greenland
Online Access:http://www.dtic.mil/docs/citations/ADA173133
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA173133
Description
Summary:This report describes a rule-driven artificial intelligence technique for automating the identification of propagation mechanisms and classification of meteor trail types on the USAF high latitude meteor burst test bed. The procedure reduces the time required to process data from one month of test bed operation from 2 staff months to about 12 hours. It is designed to emulate the procedures used by a human operator with the additional advantage of being able to use previous and future data records in the decision process. The performance of the automatic classification procedure is comparable in terms of correct decisions to human classifiers.

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