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Optimal detection with vector sensors and vector sensor line arrays

Authors: Gerald L. D’Spain; James C. Luby; Gary R. Wilson; Richard A. Gramann;

Optimal detection with vector sensors and vector sensor line arrays

Abstract

The detection performance of single vector sensors and vector sensor line arrays is degraded by nonacoustic self-noise and spatial coherence of the noise between vector sensor components. Results based on optimizing the directivity index for a single vector sensor show that the particle motion channels should always be included in the processing for optimal detection, regardless of self-noise level, assuming these levels are properly taken into account. The vector properties of acoustic intensity can be used to estimate the levels of nonacoustic noise in ocean measurements. Application of conventional, minimum variance distortionless response, and white-noise-constrained adaptive beamforming methods with ocean acoustic data collected by a vector sensor illustrates increase in spatial resolution but corresponding decrease in beamformer output and introduction of bias with increasing beamformer adaptivity. Expressions for the spatial coherence of all pairs of vector sensor components in homogeneous, isotropic noise show that significant coherence exists at half-wavelength spacing between particle motion components. For angular intervals about broadside, an equal spacing of about one wavelength for all components provides maximum directivity index, whereas each of the component spacings should be different to optimize the directivity index for angular intervals about endfire. [Work supported by ONR.]

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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