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Near-field localization of acoustic sources with imperfect spatial coherence, distributed processing, and low communication bandwidth

Multiple sensor arrays distributed over a region provide the means for accurate localization of the (x,y) position of a source. When microphone arrays are used to measure aeroacoustic signals from ground vehicles, random fluctuations in the air lead to frequency-selective coherence of the signals that arrive at widely-separated arrays. We have shown previously that even in cases of imperfect spatial coherence, improvements in source localization accuracy are possible when the data from widely-separated arrays are processed jointly by a fusion center. Further, we have shown that a distributed processing scheme involving bearing estimation at individual arrays and time-delay estimation (TDE) between pairs of widely-separated sensors performs nearly as well as the optimum scheme, with significantly lower communication bandwidth. These results were obtained by studying the Cramer-Rao bound (CRB) on source localization accuracy based on a statistical model for the data measured at the sensors. Refined bounds (Ziv-Zakai) are presented in this paper that imply a threshold value of coherence is needed to achieve accurate TDE between widely-separated sensors. The threshold coherence is a function of the signal to noise ratio, fractional bandwidth, and time-bandwidth product of the observed signals. Results are presented from measured aeroacoustic data that illustrate TDE with widely-separated sensors.