Precipitation Doppler Spectrum Reconstruction With Gaussian Process Prior

Conference paper (2024)

Authors

T.K. Dash Microwave Sensing, Signals & Systems - EEMCS
J.N. Driessen Microwave Sensing, Signals & Systems - EEMCS
O.A. Krasnov Microwave Sensing, Signals & Systems - EEMCS
Alexander Yarovoy Microwave Sensing, Signals & Systems - EEMCS
Research Group
Microwave Sensing, Signals & Systems (EEMCS) (TU Delft)
Copyright: © 2024 T.K. Dash, J.N. Driessen, O.A. Krasnov, Alexander Yarovoy
DOI
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https://doi.org/10.1109/CAMA57522.2023.10352683
Bayesian Inference Weather Doppler Radar
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Published Date

2024

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Microwave Sensing, Signals & Systems

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.