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Bias-Constrained H ₂ Optimal Finite Impulse Response Filtering for Object Tracking Under Disturbances and Data Errors.

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Title: Bias-Constrained H ₂ Optimal Finite Impulse Response Filtering for Object Tracking Under Disturbances and Data Errors.
Authors: Pale-Ramon, Eli G.1 (AUTHOR) eg.paleramon@ugto.mx, Shmaliy, Yuriy S.1 (AUTHOR) shmaliy@ugto.mx, Andrade-Lucio, Jose A.1 (AUTHOR) andrade@ugto.mx, Morales-Mendoza, Luis J.2 (AUTHOR) javmorales@uv.mx
Source: IEEE Transactions on Control Systems Technology. Jul2022, Vol. 30 Issue 4, p1782-1789. 8p.
Subjects: Tracking algorithms, Discrete time filters, Finite impulse response filters, Impulse response, Global Positioning System, Linear matrix inequalities, Euler method, Transfer functions
Abstract: The H2 finite impulse response (FIR) filtering approach allows for optimal object tracking under harsh industrial conditions. In this brief, we propose a bias-constrained H2 optimal unbiased FIR (H2-OUFIR) filter for linear discrete time-invariant systems under bounded disturbances, data errors, and initial errors. The H2-OUFIR filter is derived using the backward Euler method by minimizing the squared Frobenius norm of the weighted transfer function. A bias-constrained suboptimal H2 FIR filtering algorithm using a linear matrix inequality (LMI) is also designed. Based on experimental examples of global positioning system (GPS)-based vehicle tracking and video human tracking, it is shown that the batch H2-OUFIR filter operating on short horizons with full error matrices is able to outperform the Kalman, optimal finite impulse response (OFIR), and unbiased finite impulse response (UFIR) filters. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Control Systems Technology is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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An: 157687873
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  Data: Bias-Constrained H ₂ Optimal Finite Impulse Response Filtering for Object Tracking Under Disturbances and Data Errors.
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  Data: <searchLink fieldCode="AR" term="%22Pale-Ramon%2C+Eli+G%2E%22">Pale-Ramon, Eli G.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> eg.paleramon@ugto.mx</i><br /><searchLink fieldCode="AR" term="%22Shmaliy%2C+Yuriy+S%2E%22">Shmaliy, Yuriy S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> shmaliy@ugto.mx</i><br /><searchLink fieldCode="AR" term="%22Andrade-Lucio%2C+Jose+A%2E%22">Andrade-Lucio, Jose A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> andrade@ugto.mx</i><br /><searchLink fieldCode="AR" term="%22Morales-Mendoza%2C+Luis+J%2E%22">Morales-Mendoza, Luis J.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> javmorales@uv.mx</i>
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  Data: <searchLink fieldCode="DE" term="%22Tracking+algorithms%22">Tracking algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Discrete+time+filters%22">Discrete time filters</searchLink><br /><searchLink fieldCode="DE" term="%22Finite+impulse+response+filters%22">Finite impulse response filters</searchLink><br /><searchLink fieldCode="DE" term="%22Impulse+response%22">Impulse response</searchLink><br /><searchLink fieldCode="DE" term="%22Global+Positioning+System%22">Global Positioning System</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+matrix+inequalities%22">Linear matrix inequalities</searchLink><br /><searchLink fieldCode="DE" term="%22Euler+method%22">Euler method</searchLink><br /><searchLink fieldCode="DE" term="%22Transfer+functions%22">Transfer functions</searchLink>
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  Data: The H2 finite impulse response (FIR) filtering approach allows for optimal object tracking under harsh industrial conditions. In this brief, we propose a bias-constrained H2 optimal unbiased FIR (H2-OUFIR) filter for linear discrete time-invariant systems under bounded disturbances, data errors, and initial errors. The H2-OUFIR filter is derived using the backward Euler method by minimizing the squared Frobenius norm of the weighted transfer function. A bias-constrained suboptimal H2 FIR filtering algorithm using a linear matrix inequality (LMI) is also designed. Based on experimental examples of global positioning system (GPS)-based vehicle tracking and video human tracking, it is shown that the batch H2-OUFIR filter operating on short horizons with full error matrices is able to outperform the Kalman, optimal finite impulse response (OFIR), and unbiased finite impulse response (UFIR) filters. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IEEE Transactions on Control Systems Technology is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1109/TCST.2021.3118321
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      – Code: eng
        Text: English
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        PageCount: 8
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    Subjects:
      – SubjectFull: Tracking algorithms
        Type: general
      – SubjectFull: Discrete time filters
        Type: general
      – SubjectFull: Finite impulse response filters
        Type: general
      – SubjectFull: Impulse response
        Type: general
      – SubjectFull: Global Positioning System
        Type: general
      – SubjectFull: Linear matrix inequalities
        Type: general
      – SubjectFull: Euler method
        Type: general
      – SubjectFull: Transfer functions
        Type: general
    Titles:
      – TitleFull: Bias-Constrained H ₂ Optimal Finite Impulse Response Filtering for Object Tracking Under Disturbances and Data Errors.
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            NameFull: Pale-Ramon, Eli G.
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            NameFull: Shmaliy, Yuriy S.
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            NameFull: Andrade-Lucio, Jose A.
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            NameFull: Morales-Mendoza, Luis J.
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              Text: Jul2022
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              Y: 2022
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