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Proceedings Paper

Signal processor for acoustic sensors on UAV platforms and ground vehicles
Author(s): Ronald A. Wagstaff
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Paper Abstract

A signal processing model is presented for acoustic sensors on ground and unmanned aerial vehicles (UAV). Such sensors normally experience more flow noise than stationary sensors, because moving platforms must vary their velocity to accomplish their missions. In the case of the UAV, this includes sufficient speed to remain airborne. Unfortunately, high airflow speeds over the sensor cause turbulence noise that tends to confound the acoustic detection of signals from sources of interest on the ground. This model transforms the fluctuations in the magnitudes and the phase angles of signals and turbulence noise. The temporal coherences of the signals are improved to the point where detections can be made unambiguously, and be based on temporal coherence rather than on the signal-to-noise ratio, which is the customary way to detect signals. Additionally, because the flow noise is temporally incoherent, it is easily discriminated against. The model transforms phase and amplitude fluctuations in a such a manner that the temporal coherences of the signals are increased. This makes them more easily exploited to achieve signal processing gains, such as increases in signal-to-noise ratio and automatic detection. The rationale for this model is that both signal and noise posses magnitude, but only signals posses temporal coherence. Two transformations are presented herein. One transforms the phase angles, and the other one transforms the spectral amplitudes. The transformations give the amplitudes and phase angles similar exploitable coherence characteristics, while the corresponding noise incoherence is easily attenuated.

Paper Details

Date Published: 30 April 2007
PDF: 11 pages
Proc. SPIE 6546, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IV, 654603 (30 April 2007); doi: 10.1117/12.717941
Show Author Affiliations
Ronald A. Wagstaff, National Ctr. for Physical Acoustics (United States)


Published in SPIE Proceedings Vol. 6546:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IV
Daniel J. Henry, Editor(s)

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