Localizing Sources Using a Network of Synchronized Compact Arrays
Ildar R. Urazghildiiev, David Hannay
Abstract
Ildar R. Urazghildiiev, David Hannay
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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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