A helicopter in action is a big threat to soldiers. It can suddenly appear behind hills, vegetation etc. It would be a great advantage in being able to recognize the helicopter. One way to do this is to use the helicopter's characteristic sound, which can be unrecognizible for human ears and/or disturbed by other signals. Two different signal processing methods have been studied. An algorithm, which seeks out the characteristics in the acoustic signal of a helicopter power spectrum has been implemented. The characteristics of the acoustic signal come from the rotor blades of the helicopter. Filters that extract the characteristics of the acoustic signal of a Helicopter 9 have been designed. Cross correlation is used to compare the unknown signal with the signal of a Helicopter 9. Literature on the characteristics of helicopter sound and systems tested earlier for helicopter detection, identification and direction has been studied. Both methods (algorithm or filter) can identify the helicopter when it is hovering, but none of the methods are flexible enough to identify the helicopter at every stage. The signal processing methods have imperfections and the recordings were noisy. The software MATLAB was used for the signal processing.
Nagra Signalbehandlingsmetoder foer Helikopterupptaeckt (Some Signal Processing Methods for Positive Helicopter Identification)
1992
36 pages
Report
Keine Angabe
Englisch
Acoustic Detection , Antiaircraft Defense Systems , Air defense , Signal processing , Helicopters , Acoustic signatures , Aerodynamic noise , Acoustic detection , Spectrum analysis , Computer programs , Aircraft noise , Sound transmission , Acoustic measurement , Sound waves , Algorithms , Acoustic filters , Foreign technology