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3D TDOA Emitter Localization Using Conic Approximation

This paper develops a new time difference of arrival (TDOA) emitter localization algorithm in the 3D space, employing conic approximations of hyperboloids associated with TDOA measurements. TDOA measurements are first converted to 1D angle of arrival (1D-AOA) measurements that define TDOA cones cent...

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Detalles Bibliográficos
Autores principales: Dogancay, Kutluyil, Hmam, Hatem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383734/
https://www.ncbi.nlm.nih.gov/pubmed/37514549
http://dx.doi.org/10.3390/s23146254
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author Dogancay, Kutluyil
Hmam, Hatem
author_facet Dogancay, Kutluyil
Hmam, Hatem
author_sort Dogancay, Kutluyil
collection PubMed
description This paper develops a new time difference of arrival (TDOA) emitter localization algorithm in the 3D space, employing conic approximations of hyperboloids associated with TDOA measurements. TDOA measurements are first converted to 1D angle of arrival (1D-AOA) measurements that define TDOA cones centred about axes connecting the corresponding TDOA sensor pairs. Then, the emitter location is calculated from the triangulation of 1D-AOAs, which is formulated as a system of nonlinear equations and solved by a low-complexity two-stage estimation algorithm composed of an iterative weighted least squares (IWLS) estimator and a Taylor series estimator aimed at refining the IWLS estimate. Important conclusions are reached about the optimality of sensor–emitter and sensor array geometries. The approximate efficiency of the IWLS estimator is also established under mild conditions. The new two-stage estimator is shown to be capable of outperforming the maximum likelihood estimator while performing very close to the Cramer Rao lower bound in poor sensor–emitter geometries and large noise by way of numerical simulations.
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spelling pubmed-103837342023-07-30 3D TDOA Emitter Localization Using Conic Approximation Dogancay, Kutluyil Hmam, Hatem Sensors (Basel) Article This paper develops a new time difference of arrival (TDOA) emitter localization algorithm in the 3D space, employing conic approximations of hyperboloids associated with TDOA measurements. TDOA measurements are first converted to 1D angle of arrival (1D-AOA) measurements that define TDOA cones centred about axes connecting the corresponding TDOA sensor pairs. Then, the emitter location is calculated from the triangulation of 1D-AOAs, which is formulated as a system of nonlinear equations and solved by a low-complexity two-stage estimation algorithm composed of an iterative weighted least squares (IWLS) estimator and a Taylor series estimator aimed at refining the IWLS estimate. Important conclusions are reached about the optimality of sensor–emitter and sensor array geometries. The approximate efficiency of the IWLS estimator is also established under mild conditions. The new two-stage estimator is shown to be capable of outperforming the maximum likelihood estimator while performing very close to the Cramer Rao lower bound in poor sensor–emitter geometries and large noise by way of numerical simulations. MDPI 2023-07-09 /pmc/articles/PMC10383734/ /pubmed/37514549 http://dx.doi.org/10.3390/s23146254 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Dogancay, Kutluyil
Hmam, Hatem
3D TDOA Emitter Localization Using Conic Approximation
title 3D TDOA Emitter Localization Using Conic Approximation
title_full 3D TDOA Emitter Localization Using Conic Approximation
title_fullStr 3D TDOA Emitter Localization Using Conic Approximation
title_full_unstemmed 3D TDOA Emitter Localization Using Conic Approximation
title_short 3D TDOA Emitter Localization Using Conic Approximation
title_sort 3d tdoa emitter localization using conic approximation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383734/
https://www.ncbi.nlm.nih.gov/pubmed/37514549
http://dx.doi.org/10.3390/s23146254
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