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

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.