M. Grecu et Wf. Krajewski, Detection of anomalous propagation echoes in weather radar data using neural networks, IEEE GEOSCI, 37(1), 1999, pp. 287-296
Citations number
19
Categorie Soggetti
Eletrical & Eletronics Engineeing
Journal title
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
We investigate a neural network-based methodology for detection of the anom
alous propagation (AP) radar echo. The methodology is devised to cope with
the situations when only single scan data are available. The output of the
procedure is quantified in four classes corresponding to the upper limits o
f 25, 50, 75, and 100% of AP echo per scan, The high dimension of the input
data space is reduced by feature extraction based on physical consideratio
ns. Fractal based, statistical, and wavelet analyses are performed, and the
ir characteristics are used as features. A feedforward neural network is us
ed for classification in the four classes, with a fuzzy strategy used in th
e network training. We test the methodology on real data and make a compreh
ensive assessment of the procedure's accuracy based on cross validation.