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Tracking Multiple Targets Using Bearing-Only Measurements in Underwater Noisy Environments

This article handles tracking multiple targets using bearing-only measurements in underwater noisy environments. For tracking multiple targets in underwater noisy environments, the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter provides good performance with its low computational lo...

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Detalles Bibliográficos
Autor principal: Kim, Jonghoek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370893/
https://www.ncbi.nlm.nih.gov/pubmed/35898016
http://dx.doi.org/10.3390/s22155512
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author Kim, Jonghoek
author_facet Kim, Jonghoek
author_sort Kim, Jonghoek
collection PubMed
description This article handles tracking multiple targets using bearing-only measurements in underwater noisy environments. For tracking multiple targets in underwater noisy environments, the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter provides good performance with its low computational load. Bearing-only measurements are passive and do not provide position information of a target. Note that the nonlinearity of the bearing-only measurements can be handled by Extended Kalman Filters (EKF) when applying the GM-PHD filter. However, range uncertainty of the target is large for bearing-only measurements. Thus, a single EKF leads to poor performance when it is applied in the GM-PHD. In this article, every bearing measurement gives birth to multiple target samples, which are distributed considering the feasible range of the passive sensor. Thereafter, every target sample is updated utilizing the measurement update step of the EKF. In this way, we run multiple EKFs associated to multiple target samples, instead of running a single EKF. To the best of our knowledge, our article is novel in tracking multiple targets in noisy environments, using the observer with bearing-only measurements. The effectiveness of the proposed GM-PHD is verified utilizing MATLAB simulations.
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spelling pubmed-93708932022-08-12 Tracking Multiple Targets Using Bearing-Only Measurements in Underwater Noisy Environments Kim, Jonghoek Sensors (Basel) Article This article handles tracking multiple targets using bearing-only measurements in underwater noisy environments. For tracking multiple targets in underwater noisy environments, the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter provides good performance with its low computational load. Bearing-only measurements are passive and do not provide position information of a target. Note that the nonlinearity of the bearing-only measurements can be handled by Extended Kalman Filters (EKF) when applying the GM-PHD filter. However, range uncertainty of the target is large for bearing-only measurements. Thus, a single EKF leads to poor performance when it is applied in the GM-PHD. In this article, every bearing measurement gives birth to multiple target samples, which are distributed considering the feasible range of the passive sensor. Thereafter, every target sample is updated utilizing the measurement update step of the EKF. In this way, we run multiple EKFs associated to multiple target samples, instead of running a single EKF. To the best of our knowledge, our article is novel in tracking multiple targets in noisy environments, using the observer with bearing-only measurements. The effectiveness of the proposed GM-PHD is verified utilizing MATLAB simulations. MDPI 2022-07-24 /pmc/articles/PMC9370893/ /pubmed/35898016 http://dx.doi.org/10.3390/s22155512 Text en © 2022 by the author. 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
Kim, Jonghoek
Tracking Multiple Targets Using Bearing-Only Measurements in Underwater Noisy Environments
title Tracking Multiple Targets Using Bearing-Only Measurements in Underwater Noisy Environments
title_full Tracking Multiple Targets Using Bearing-Only Measurements in Underwater Noisy Environments
title_fullStr Tracking Multiple Targets Using Bearing-Only Measurements in Underwater Noisy Environments
title_full_unstemmed Tracking Multiple Targets Using Bearing-Only Measurements in Underwater Noisy Environments
title_short Tracking Multiple Targets Using Bearing-Only Measurements in Underwater Noisy Environments
title_sort tracking multiple targets using bearing-only measurements in underwater noisy environments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370893/
https://www.ncbi.nlm.nih.gov/pubmed/35898016
http://dx.doi.org/10.3390/s22155512
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