An automatic identification of clutter and anomalous propagation in polarization-diversity weather radar data using neural networks

IEEE Transactions on Geoscience and Remote Sensing

Volumn 39, Issue 8, 2001, Pages 1777-1788

  Da Silveira, Reinaldo B ^a   Holt, Anthony Roy ^b  

^a CEP 70610 400   (Brazil)

^b UNIVERSITY OF ESSEX   (United Kingdom)

Author keywords

Clutter; Neural network; Polarization diversity; Precipitation; Radar

Indexed keywords

FEEDFORWARD NEURAL NETWORKS; LIGHT POLARIZATION; LIGHT PROPAGATION; REMOTE SENSING; WEATHERING;

ANOMALOUS PROPAGATION;

RADAR CLUTTER;

EID: 0035444780     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/36.942556     Document Type: Article

References (32)

1. Ground clutter characteristics and residue mapping
2. Techniques for automatic ground clutter rejection
3. Intensity measurement of precipitation echo superposed on ground clutter-A new automatic technique for ground clutter rejection
4. Ground clutter rejection in the frequency domain
5. The use of Doppler and polarization data to identify ground clutter and ANAPROP
6. Detection of anomalous propagation echoes in weather radar data using neural networks
7. Rainfall and clutter discrimination by means of dual-linear polarization radar measurements
8. Polarimetric rainfall estimation in the presence of anomalous propagation
9. Cloud micro-physics retrieval using s-band dual-polarization radar measurements
10. Principles for the radar determination of the polarization properties of precipitation
11. Some factors affecting the remote sensing of rain by polarization diversity radar in the 3- to 35-GHz frequency range
12. The extraction of rainrates from CDR data
13. Separation of propagation and backscattering effects in rain for circular polarization diversity S-band radars
14. Correction of propagation effects in S-Band circular polarization-diversity radars
15. Relationship of differential reflectivity to correlation in dual-polarization radar
16. Extraction of differential propagation phase from data from S-band circularly polarized radars
17. On the use of polarization-diversity to aid recognition of ground clutter and anomalous propagation in radar echoes of storms
18. Classification of radar clutter using neural networks
19. A knowledge based color graphics display system for multi-parameter weather radar data
20. An introduction to computing with neural networks