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Ground clutter characterization and elimination in mountainous terrain

Authors: GABELLA, MARCO; NOTARPIETRO, RICCARDO;

Ground clutter characterization and elimination in mountainous terrain

Abstract

A simple and fast texture-based technique for the removal of residual ground clutter is presented. Its main advantages are that it is easy to implement (both for polar and Cartesian data) and can be applied a posteriori after any other method of clutter removal has been applied. The performances of the technique during clear-sky and rainy conditions are analyzed for a 180×150 km2 complex-orography region, using data from a non-Doppler and a Doppler radar (for both, approximately 50% of the clear-sky clutter shows average reflectivity greater than 13 dBZ). In the case of the non-Doppler data, the texture-based code is used after a prestored static map: it is absolutely necessary and leads to excellent results. In the case of the Doppler data, the technique can be applied with satisfactory results, even after a recent approach, which, in addition to a Doppler velocity test, combine all the available information concerning radar echoes.

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Italy
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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