Combining signal processing and machine leasing techniques for real time measurement of raindrop

Bruce Denby (1) , Jean-Christophe Prévotet (2) , Patrick Garda (3) , Bertrand Granado (3) , Laurent Barthès (4) , Peter Gole (4) , J. Lavergnat (4) , J.-Y. Delahaye (4)

1 SIGMA - Laboratoire Signaux, Modèles et Apprentissage Statistique
2 IETR - Institut d'Electronique et de Télécommunications de Rennes
3 LIS - Laboratoire des Instruments et Systèmes
4 CETP - Centre d'étude des environnements terrestre et planétaires

The data acquisition system for a new type of optical disdrometer is presented. As the device must measure sizes and velocities of raindrops as small as 0.1 mm diameter in real time in the presence of high noise and a variable baseline, algorithm design has been a challenge. The combining of standard signal processing techniques and machine learning methods (in this case, a neural network) has been essential to obtaining good performance.

Domaines: Architectures Matérielles [cs.AR]; Electronique

Bruce Denby, Jean-Christophe Prévotet, Patrick Garda, Bertrand Granado, Laurent Barthès, et al.. Combining signal processing and machine leasing techniques for real time measurement of raindrop. IEEE Transactions on Instrumentation and Measurement, 2001, 50 (6), pp.1717-1724. ⟨hal-01534266⟩