An artificial neural network (ANN) based helicopter identification system is proposed. The feature vectors are based on both the tonal and the broadband spectrum of the helicopter signal, ANN pattern classifiers are trained using various parametric spectral representation techniques. Specifically, linear prediction, reflection coefficients, cepstrum, and line spectral frequencies (LSF) are compared in terms of recognition accuracy and robustness against additive noise. Finally, an 8-helicopter ANN classifier is evaluated. It is also shown that the classifier performance is dramatically improved if it is trained using both clean data and data corrupted with additive noise.
Parametric models for helicopter identification using ANN
IEEE Transactions on Aerospace and Electronic Systems ; 36 , 4 ; 1242-1252
2000-10-01
727150 byte
Article (Journal)
Electronic Resource
English
Parametric models for helicopter identification using ANN
Tema Archive | 2000
|PAPERS - Parametric Models for Helicopter Identification Using ANN
Online Contents | 2000
|Identification of helicopter rotor dynamic models
AIAA | 1983
|Identification of helicopter rotor dynamic models
NTRS | 1983
|