Matched-field source localization with non-synchronized sensor arrays
Abstract
This paper considers combining information from multiple hydrophone arrays in matched-field source localization. Assuming each individual array is comprised of calibrated sensors which are synchronized in time, conventional matched-field methods can be applied for each array using the Bartlett (linear) processor and the resulting processors summed over arrays. However, if the relative calibration and/or time synchronization is known between some or all arrays, more informative multiple-array processors can be derived by maximum-likelihood methods. For example, if the relative calibration of the arrays is known, the observed amplitude variation of the received field between arrays provides additional information for source localization: the corresponding processor takes advantage of the fact that the source amplitude spectrum is the same (although unknown) for all arrays. Likewise, if synchronization between arrays is known, phase variation provides localization information. Various multiple-array processors are derived and evaluated in terms of the probability of correct localization from Monte-Carlo analyses. The analysis indicates that, dependent on array configurations, significant improvements in source localization performance can be achieved when including relative amplitude and/or phase information in multiple-array processors.
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