Code Underlying: Latent Moment Beamforming (LAMB) for Precipitation using Fast-Scanning Phased Array Weather Radars and Hamiltonian Monte Carlo (HMC)

DOI:10.4121/c3bedfcd-7326-4510-ab41-e355ff57bdcd.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/c3bedfcd-7326-4510-ab41-e355ff57bdcd

Datacite citation style

Dash, Tworit; yuan, sen; Heylen, Jonas; Yarovoy, Alexander (2025): Code Underlying: Latent Moment Beamforming (LAMB) for Precipitation using Fast-Scanning Phased Array Weather Radars and Hamiltonian Monte Carlo (HMC). Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/c3bedfcd-7326-4510-ab41-e355ff57bdcd.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This repository contains MATLAB code implementing a Latent Moment Beamforming (LAMB) technique for retrieving Doppler moments of precipitation using fast-scanning phased array weather radars. The estimation is performed using Hamiltonian Monte Carlo (HMC) to enable physically consistent inference under uncertainty.


Key Features:

  • Latent Moment Model: Represents the Doppler spectrum in terms of interpretable latent variables (mean μ, spread σ, and strength M) per beam direction.
  • Hamiltonian Monte Carlo (HMC): Performs Bayesian inference using a leapfrog-integrated sampling framework for efficient exploration of the posterior.
  • Gradient-based Likelihood: Includes analytical gradients to accelerate HMC convergence.
  • Customizable Radar Parameters: Easily adapt the code to different array geometries, scan strategies, or velocity resolutions.


History

  • 2025-07-28 first online, published, posted

Publisher

4TU.ResearchData

Format

MATLAB, *.m

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Microelectronics

DATA - restricted access

Reason

The code provided in this submission are protected under intellectual property rights owned by the original authors. To ensure proper recognition and to protect the intellectual contributions of the authors, access to these files is restricted. Users must request access and agree to the conditions outlined below.

End User Licence Agreement

License Agreement Terms

  1. Usage Rights: The dataset and code can only be accessed by users who have been granted explicit permission. Users must submit a request to gain access and explain the purpose of their use.
  2. Citation Requirement: Users granted access to the dataset and code must properly cite the original authors’ paper and any related code when using, publishing, or disseminating results derived from this data or software. The citation should follow the format provided by the authors.
  3. Non-Commercial Use: The dataset and code are to be used strictly for non-commercial research purposes unless explicit permission for commercial use is obtained from the authors.
  4. Redistribution: Users are not permitted to redistribute the dataset or code in any form. Any parties interested in using the dataset or code must follow the same request process outlined here.
  5. Modifications: Any modifications to the code or derived datasets must also be accompanied by appropriate citations and must acknowledge the original authors.
  6. Reporting Results: Users are encouraged to share their findings with the original authors and, where applicable, collaborate on publishing results.

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