Our team has introduced a groundbreaking method for measuring precipitation with phased-array radar, published in IEEE Transactions on Geoscience and Remote Sensing.

The new technique, Latent Moment Beamforming (LAMB), developed by Tworit Dash, Sen Yuan, Jonas Heylen, and Olexander Yarovoy, challenges conventional radar methodology. Instead of explicitly steering beams to specific elevations, a process that can introduce distortions, LAMB treats the entire elevation profile as a unified statistical problem. The beamforming occurs “latently” within the mathematical model itself. The technique is not just limited to profile estimation, but also estimates the uncertainty expected from the profile estimation. The paper includes a comparison of the accuracy of the estimates with the theoretical Cramer-Rao bounds (CRB). Uncertainty estimation is crucial for adaptive scan strategies in next-generation phased array weather radars.

The approach achieves more accurate vertical profiles of precipitation, particularly for systems requiring rapid updates or operating with limited antenna apertures. The research has significant implications for weather forecasting, aviation safety, and climate monitoring.