Abstract
Ground-based networks of acoustical arrays can be used to track the location of moving ground vehicles and flying aircraft. In this paper, a method is proposed for simulating the statistical accuracy of location estimates derived from array networks. The method is based on combining Cramer–Rao lower bounds for the bearing accuracy of the individual arrays, by using a general stochastic inverse formulation. Environmental phenomena associated with acoustic propagation, such as refraction by wind and temperature gradients, ground interactions, terrain masking, and signal coherence degradation by turbulence, are included in the calculations. Issues unique to sources moving at high subsonic Mach numbers, such as source radiation patterns and propagation delays, are discussed. The statistical analysis is compared to measurements made at Fort Bliss (Texas) on a small, jet-powered drone aircraft flying at 1000 feet above ground level. Differences between radar (truth) and acoustical tracking data are compared to the simulation-based predictions.
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