2021IEEE Journal of Oceanic EngineeringRequires access

Localizing Sources Using a Network of Synchronized Compact Arrays

Ildar R. Urazghildiiev, David Hannay

Open publisher page 14 citations

Abstract

The problem of passive acoustic estimating the position of a source using a network of synchronized underwater compact arrays is considered. Maximum-likelihood estimators using angle of arrival (AOA), time difference of arrival (TDOA), as well as a combination of AOA/TDOA estimates are developed. The localization accuracy provided by the AOA-based, TDOA-based, and hybrid estimators is evaluated using Cramér–Rao bounds, statistical simulations, andin situtest. Test results demonstrated that the efficiency of AOA-based and TDOA-based estimators strongly depends on variances of the AOA and TDOA estimates. Relative efficiency of the hybrid estimator is higher than any of the AOA-based and TDOA-based algorithms.

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What this paper is about

The problem of passive acoustic estimating the position of a source using a network of synchronized underwater compact arrays is considered. Maximum-likelihood estimators using angle of arrival (AOA), time difference of arrival (TDOA), as well as a combination of AOA/TDOA estimates are developed. The localization accuracy provided by the AOA-based, TDOA-based, and hybrid estimators is evaluated using Cramér–Rao bounds, statistical simulations, andin situtest. Test results demonstrated that the efficiency of AOA-based and TDOA-based estimators strongly depends on variances of the AOA and TDOA estimates. Relative efficiency of the hybrid estimator is higher than any of the AOA-based and TDOA-based algorithms.

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Available abstract

The problem of passive acoustic estimating the position of a source using a network of synchronized underwater compact arrays is considered. Maximum-likelihood estimators using angle of arrival (AOA), time difference of arrival (TDOA), as well as a combination of AOA/TDOA estimates are developed. The localization accuracy provided by the AOA-based, TDOA-based, and hybrid estimators is evaluated using Cramér–Rao bounds, statistical simulations, andin situtest. Test results demonstrated that the efficiency of AOA-based and TDOA-based estimators strongly depends on variances of the AOA and TDOA estimates. Relative efficiency of the hybrid estimator is higher than any of the AOA-based and TDOA-based algorithms.

Key concepts: Multilateration, Estimator, FDOA, Angle of arrival, Algorithm, Computer science, Cramér–Rao bound, Direction finding

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