Combining signal processing and machine learning techniques for real time measurement of raindrops

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.

[1]  P. Gole,et al.  Real time data acquisition techniques in meteorological applications , 1998 .

[2]  Lutz Hasse,et al.  An Optical Disdrometer for Use in High Wind Speeds , 1998 .

[3]  Peter Golé,et al.  TDNN Approach to Measuring Raindrop Sizes and Velocities , 1998 .

[4]  Philippe Waldteufel,et al.  A New Optical Instrument for Simultaneous Measurement of Raindrop Diameter and Fall Speed Distributions , 1984 .

[5]  Edwin Campos,et al.  Instrumental Uncertainties in Z–R Relations , 2000 .

[6]  Jose C. Principe,et al.  Neural and adaptive systems : fundamentals through simulations , 2000 .

[7]  M. Löffler-Mang,et al.  An Optical Disdrometer for Measuring Size and Velocity of Hydrometeors , 2000 .

[8]  Jose C. Principe,et al.  Neural and adaptive systems , 2000 .

[9]  J. Joss,et al.  Ein Spektrograph für Niederschlagstropfen mit automatischer Auswertung , 1967 .

[10]  G. Carter,et al.  The generalized correlation method for estimation of time delay , 1976 .

[11]  Carlton W. Ulbrich,et al.  Path- and Area-Integrated Rainfall Measurement by Microwave Attenuation in the 1–3 cm Band , 1977 .

[12]  J. Nazuno.  Haykin, Simon. Neural networks: A comprehensive foundation, Prentice Hall, Inc. Segunda Edición, 1999 , 2000 .

[13]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[14]  B. Denby,et al.  Structured neural network approach for measuring raindrop sizes and velocities , 1998, Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378).