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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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2023-07, Vol.23 (14), p.6254
Main Authors: Dogancay, Kutluyil, Hmam, Hatem
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Estimates
iterative weighted least squares
Localization
maximum likelihood estimator
Neural networks
Numerical analysis
Sensors
time difference of arrival localization
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Summary: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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s23146254