Paper
21 July 2000 Helicopter detection and classification demonstrator
Author Affiliations +
Abstract
A technology demonstrator that detects and classifies different helicopter types automatically, was developed at TNO-FEL. The demonstrator is based on a PC, which receives its acoustic input from an all-weather microphone. The demonstrator uses commercial off-the-shelf hardware to digitize the acoustic signal. The user-interface and the signal processing software are written in MatLabTM. The demonstrator detects the noise from helicopters; the classification is performed using a database with helicopter-specific features. The demonstrator currently contains information of 11 different helicopter types, but can easily be expanded to include additional types of helicopters. The input signal is analyzed in real time, the result is a classification ranging from `no target' to `helicopter type x', e.g. Lynx Mk2. If the helicopter is classified, its relative speed is estimated as well. The algorithm was developed and tested using a database of different helicopters (hovering and moving) recorded at distances ranging from 90 meter up to 8 kilometer. The sensitivity to noise was investigated using jet, tank, artillery and environmental (wind and turbulence) noise as input.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Antonius C. van Koersel "Helicopter detection and classification demonstrator", Proc. SPIE 4040, Unattended Ground Sensor Technologies and Applications II, (21 July 2000); https://doi.org/10.1117/12.392575
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Cited by 2 scholarly publications.
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KEYWORDS
Algorithm development

Acoustics

Databases

Detection and tracking algorithms

Atmospheric propagation

Human-machine interfaces

Signal detection

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