Abstract
The challenge of reconstructing the Doppler spectrum of a precipitation-like event observed by a fast-scanning weather radar is addressed. A novel method is proposed where the echo sequence in time is assumed to be a complex Gaussian process with a known covariance structure. It is a two-step approach where the first step is the estimation of the hyperparameters of the covariance function with a maximum likelihood approach, and the second step is the reconstruction of the spectrum directly in the time or spectral domain. The proposed approach is applied to simulated data for hyper-parameter estimation performance analysis and real radar data for the complete Doppler spectrum reconstruction.
| Original language | English |
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| Title of host publication | 2023 IEEE Conference on Antenna Measurements and Applications, CAMA 2023 |
| Pages | 909-914 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350323047 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | IEEE International Conference on Antenna Measurements and Applications - Genoa, Italy Duration: 15 Nov 2023 → 16 Nov 2023 |
Publication series
| Name | IEEE Conference on Antenna Measurements and Applications, CAMA |
|---|---|
| ISSN (Print) | 2474-1760 |
| ISSN (Electronic) | 2643-6795 |
Conference
| Conference | IEEE International Conference on Antenna Measurements and Applications |
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| Abbreviated title | IEEE CAMA 2023 |
| Country/Territory | Italy |
| City | Genoa |
| Period | 15/11/23 → 16/11/23 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- Bayesian Inference
- Weather Doppler Radar