Journal article
An Efficient Methodology for Detection of Anomalous Propagation Echoes in Radar Reflectivity Data Using Neural Networks
Journal of atmospheric and oceanic technology, Vol.17(2), pp.121-129
02/2000
DOI: 10.1175/1520-0426(2000)017<0121:AEMFDO>2.0.CO;2
Abstract
To detect anomalous propagation echoes in radar data, an automated procedure based on a neural network classification scheme has been developed. Earlier results had indicated that algorithms used to detect anomalous propagation must be calibrated before they can be applied to new sites. Developing a calibration dataset is typically laborious as it involves a human expert. To eliminate this problem, an efficient methodology of calibrating and validating neural network–based detection is proposed. Using volume scan radar reflectivity data from two WSR-88D locations, the authors demonstrate that the procedure can be calibrated easily and applied successfully to different sites.
Details
- Title: Subtitle
- An Efficient Methodology for Detection of Anomalous Propagation Echoes in Radar Reflectivity Data Using Neural Networks
- Creators
- Mircea GrecuWitold F Krajewski
- Resource Type
- Journal article
- Publication Details
- Journal of atmospheric and oceanic technology, Vol.17(2), pp.121-129
- DOI
- 10.1175/1520-0426(2000)017<0121:AEMFDO>2.0.CO;2
- ISSN
- 0739-0572
- eISSN
- 1520-0426
- Language
- English
- Date published
- 02/2000
- Academic Unit
- Civil and Environmental Engineering
- Record Identifier
- 9983991986602771
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