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Distributed localization using Levenberg-Marquardt algorithm
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- Ahmadi, Shervin Parvini (author)
- Linköpings universitet,Reglerteknik,Tekniska fakulteten
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- Hansson, Anders (author)
- Linköpings universitet,Reglerteknik,Tekniska fakulteten
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- Pakazad, Sina Khoshfetrat (author)
- C3 Ai, CA USA
- (creator_code:org_t)
- 2021-08-23
- 2021
- English.
- In: EURASIP Journal on Advances in Signal Processing. - : SPRINGER. - 1687-6172 .- 1687-6180. ; 2021:1
- Journal article (peer-reviewed)
Abstract
Subject headings
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- In this paper, we propose a distributed algorithm for sensor network localization based on a maximum likelihood formulation. It relies on the Levenberg-Marquardt algorithm where the computations are distributed among different computational agents using message passing, or equivalently dynamic programming. The resulting algorithm provides a good localization accuracy, and it converges to the same solution as its centralized counterpart. Moreover, it requires fewer iterations and communications between computational agents as compared to first-order methods. The performance of the algorithm is demonstrated with extensive simulations in Julia in which it is shown that our method outperforms distributed methods that are based on approximate maximum likelihood formulations.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
Keyword
- Distributed localization; Maximum likelihood estimation; Message passing; Dynamic programming; Levenberg-Marquardt; Nonlinear least-squares
Publication and Content Type
- ref (subject category)
- art (subject category)
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