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V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction

Trajectory reconstruction is the process of inferring the path of a moving object between successive observations. In this paper, we propose a smoothing spline—which we name the V-spline—that incorporates position and velocity information and a penalty term that controls acceleration. We introduce a...

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Detalles Bibliográficos
Autores principales: Cao, Zhanglong, Bryant, David, Molteno, Timothy C.A., Fox, Colin, Parry, Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125788/
https://www.ncbi.nlm.nih.gov/pubmed/34066396
http://dx.doi.org/10.3390/s21093215
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author Cao, Zhanglong
Bryant, David
Molteno, Timothy C.A.
Fox, Colin
Parry, Matthew
author_facet Cao, Zhanglong
Bryant, David
Molteno, Timothy C.A.
Fox, Colin
Parry, Matthew
author_sort Cao, Zhanglong
collection PubMed
description Trajectory reconstruction is the process of inferring the path of a moving object between successive observations. In this paper, we propose a smoothing spline—which we name the V-spline—that incorporates position and velocity information and a penalty term that controls acceleration. We introduce an adaptive V-spline designed to control the impact of irregularly sampled observations and noisy velocity measurements. A cross-validation scheme for estimating the V-spline parameters is proposed, and, in simulation studies, the V-spline shows superior performance to existing methods. Finally, an application of the V-spline to vehicle trajectory reconstruction in two dimensions is given, in which the penalty term is allowed to further depend on known operational characteristics of the vehicle.
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spelling pubmed-81257882021-05-17 V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction Cao, Zhanglong Bryant, David Molteno, Timothy C.A. Fox, Colin Parry, Matthew Sensors (Basel) Article Trajectory reconstruction is the process of inferring the path of a moving object between successive observations. In this paper, we propose a smoothing spline—which we name the V-spline—that incorporates position and velocity information and a penalty term that controls acceleration. We introduce an adaptive V-spline designed to control the impact of irregularly sampled observations and noisy velocity measurements. A cross-validation scheme for estimating the V-spline parameters is proposed, and, in simulation studies, the V-spline shows superior performance to existing methods. Finally, an application of the V-spline to vehicle trajectory reconstruction in two dimensions is given, in which the penalty term is allowed to further depend on known operational characteristics of the vehicle. MDPI 2021-05-06 /pmc/articles/PMC8125788/ /pubmed/34066396 http://dx.doi.org/10.3390/s21093215 Text en © 2021 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
Cao, Zhanglong
Bryant, David
Molteno, Timothy C.A.
Fox, Colin
Parry, Matthew
V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction
title V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction
title_full V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction
title_fullStr V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction
title_full_unstemmed V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction
title_short V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction
title_sort v-spline: an adaptive smoothing spline for trajectory reconstruction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125788/
https://www.ncbi.nlm.nih.gov/pubmed/34066396
http://dx.doi.org/10.3390/s21093215
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