KEYWORDS: Acoustics, 3D modeling, Global Positioning System, Data modeling, 3D acquisition, Signal processing, Detection and tracking algorithms, Error analysis, Sensors, Unattended ground sensors
Networks of unattended acoustic ground sensors can be used to detect and accurately track high-speed airborne acoustic sources. While it is possible, in principle, to estimate altitude using networks of two-dimensional microphone arrays, the high sensitivity of this configuration significantly limits performance. This work shows that the addition of elevated microphones and appropriate signal processing can significantly improve performance. Airborne source tracking results from a field experiment are compared for the use of a small orthogonal three-microphone ground plane array versus the same array with an elevated microphone added.
KEYWORDS: Acoustics, Missiles, 3D acquisition, Wavefronts, Numerical analysis, Solids, Signal to noise ratio, Data centers, IRIS Consortium, Seismic sensors
It is well known that lines of bearing to an airborne broadband target can be easily measured on a small ground-based array of microphones. With a stationary target and two arrays, the target location can be estimated by direct triangulation, i.e., by the crossing point of bearing lines. With a moving source, however, one must identify arrival times on the arrays that correspond to a common emission point or, equivalently, a common emission time. This paper shows that, with two arrays, the three-dimensional track of a moving airborne target can be determined by finding the stationary points of an iterative non-linear equation. The equation is of the form (tau) geo((tau) bt) equals (tau) 'bt where (tau) geo is the difference in travel times determined from geometry, (tau) bt is the travel time difference taken from the bearing-time curves for two different arrays, and (tau) bt is the estimated value for (tau) bt. The stationary points, i.e., where (tau) geo equals (tau) bt, allow the target track to be computed directly from triangulation. Examples are discussed using simulated data.
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