A Novel Smooth Variable Structure Smoother for Robust Estimation

The smooth variable structure filter (SVSF) is a new-type filter based on the sliding-mode concepts and has good stability and robustness in overcoming the modeling uncertainties and errors. However, SVSF is insufficient to suppress Gaussian noise. A novel smooth variable structure smoother (SVSS) b...

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Main Authors: Yu Chen, Luping Xu, Bo Yan, Cong Li
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/6/1781
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author Yu Chen
Luping Xu
Bo Yan
Cong Li
author_facet Yu Chen
Luping Xu
Bo Yan
Cong Li
author_sort Yu Chen
collection DOAJ
description The smooth variable structure filter (SVSF) is a new-type filter based on the sliding-mode concepts and has good stability and robustness in overcoming the modeling uncertainties and errors. However, SVSF is insufficient to suppress Gaussian noise. A novel smooth variable structure smoother (SVSS) based on SVSF is presented here, which mainly focuses on this drawback and improves the SVSF estimation accuracy of the system. The estimation of the linear Gaussian system state based on SVSS is divided into two steps: Firstly, the SVSF state estimate and covariance are computed during the forward pass in time. Then, the smoothed state estimate is computed during the backward pass by using the innovation of the measured values and covariance estimate matrix. According to the simulation results with respect to the maneuvering target tracking, SVSS has a better performance compared with another smoother based on SVSF and the Kalman smoother in different tracking scenarios. Therefore, the SVSS proposed in this paper could be widely applied in the field of state estimation in dynamic system.
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spelling doaj.art-7d2e001ce05644d2b040d50c322783322022-12-22T02:57:51ZengMDPI AGSensors1424-82202020-03-01206178110.3390/s20061781s20061781A Novel Smooth Variable Structure Smoother for Robust EstimationYu Chen0Luping Xu1Bo Yan2Cong Li3School of Aerospace Science and Technology, Xidian University, Xi’an 710126, ChinaSchool of Aerospace Science and Technology, Xidian University, Xi’an 710126, ChinaSchool of Aerospace Science and Technology, Xidian University, Xi’an 710126, ChinaAcademy of Space Electronic Information Technology, Xi’an 710100, ChinaThe smooth variable structure filter (SVSF) is a new-type filter based on the sliding-mode concepts and has good stability and robustness in overcoming the modeling uncertainties and errors. However, SVSF is insufficient to suppress Gaussian noise. A novel smooth variable structure smoother (SVSS) based on SVSF is presented here, which mainly focuses on this drawback and improves the SVSF estimation accuracy of the system. The estimation of the linear Gaussian system state based on SVSS is divided into two steps: Firstly, the SVSF state estimate and covariance are computed during the forward pass in time. Then, the smoothed state estimate is computed during the backward pass by using the innovation of the measured values and covariance estimate matrix. According to the simulation results with respect to the maneuvering target tracking, SVSS has a better performance compared with another smoother based on SVSF and the Kalman smoother in different tracking scenarios. Therefore, the SVSS proposed in this paper could be widely applied in the field of state estimation in dynamic system.https://www.mdpi.com/1424-8220/20/6/1781robust estimationsmooth variable structure filterkalman smoothertarget trackinguncertain system
spellingShingle Yu Chen
Luping Xu
Bo Yan
Cong Li
A Novel Smooth Variable Structure Smoother for Robust Estimation
Sensors
robust estimation
smooth variable structure filter
kalman smoother
target tracking
uncertain system
title A Novel Smooth Variable Structure Smoother for Robust Estimation
title_full A Novel Smooth Variable Structure Smoother for Robust Estimation
title_fullStr A Novel Smooth Variable Structure Smoother for Robust Estimation
title_full_unstemmed A Novel Smooth Variable Structure Smoother for Robust Estimation
title_short A Novel Smooth Variable Structure Smoother for Robust Estimation
title_sort novel smooth variable structure smoother for robust estimation
topic robust estimation
smooth variable structure filter
kalman smoother
target tracking
uncertain system
url https://www.mdpi.com/1424-8220/20/6/1781
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