DocumentCode :
3697428
Title :
Feature extraction for acoustic classification of small aircraft
Author :
Alexander Yakubovskiy;Hady Salloum;Alexander Sutin;Alexander Sedunov;Nikolay Sedunov;David Masters
Author_Institution :
Stevens Institute of Technology Castle Point on Hudson, Hoboken, NJ 07030, USA
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
Standard approach to aircraft classification in acoustic sensor networks is based on propeller blades rotation harmonics and fundamental frequency analysis. However, propeller blades induced sound is not the only sound producing mechanism. As a result, aircraft of different classes (small plane, helicopter, and ultralight aircraft) often provide similar acoustic signatures in the spectral domain. We present new feature extraction methods beyond the spectral peaks-based ones. First, general feature extraction considerations are reviewed. Then features are described including harmonic-based feature, a feature based on Lloyd´s mirror multi-path propagation effect, and a feature based on sound spikes caused by propeller blades interaction with flow vortices. Experiments are provided to justify the efficiency of the proposed features for target classification.
Publisher :
ieee
Conference_Titel :
Applications of Signal Processing to Audio and Acoustics (WASPAA), 2015 IEEE Workshop on
Type :
conf
DOI :
10.1109/WASPAA.2015.7336911
Filename :
7336911
Link To Document :
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