Strong-tracking multiple model estimator

Yan Liang; Quan Pan; Yu Gang Jia; Dong Hua Zhou

Strong-tracking multiple model estimator

Yan Liang, Quan Pan, Yu Gang Jia, Dong Hua Zhou

Tsinghua University

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

Firstly we analyse the properties of Strong Tracking Filter (STF) and Interacting Multiple Model(IMM) algorithm and find that STF is a parameter-adaptive algorithm and IMM is a model-adaptive algorithm. It means that they may be combined effectively. Secondly we propose a new method based on the Least-Squared Estimation to search for the fading factor in STF. After that, we design a Strong-Tracking Multiple Model Estimator (STMME) by combining the new STF with IMM. Finally, the simulation show that STMME greatly improves accuracy of velocity and acceleration compared with the conventional IMM when tracking the maneuvering target. And the computation burden increase only 6%.

Original language	English
Pages (from-to)	34-37
Number of pages	4
Journal	Tien Tzu Hsueh Pao/Acta Electronica Sinica
Volume	30
Issue number	1
State	Published - Jan 2001
Externally published	Yes

Keywords

Fault detection
Interacting multiple model algorithm
Strong tracking filter
Tracking maneuvering targets

Cite this

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title = "Strong-tracking multiple model estimator",

abstract = "Firstly we analyse the properties of Strong Tracking Filter (STF) and Interacting Multiple Model(IMM) algorithm and find that STF is a parameter-adaptive algorithm and IMM is a model-adaptive algorithm. It means that they may be combined effectively. Secondly we propose a new method based on the Least-Squared Estimation to search for the fading factor in STF. After that, we design a Strong-Tracking Multiple Model Estimator (STMME) by combining the new STF with IMM. Finally, the simulation show that STMME greatly improves accuracy of velocity and acceleration compared with the conventional IMM when tracking the maneuvering target. And the computation burden increase only 6%.",

keywords = "Fault detection, Interacting multiple model algorithm, Strong tracking filter, Tracking maneuvering targets",

author = "Yan Liang and Quan Pan and Jia, {Yu Gang} and Zhou, {Dong Hua}",

year = "2001",

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language = "英语",

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T1 - Strong-tracking multiple model estimator

AU - Liang, Yan

AU - Pan, Quan

AU - Jia, Yu Gang

AU - Zhou, Dong Hua

PY - 2001/1

Y1 - 2001/1

N2 - Firstly we analyse the properties of Strong Tracking Filter (STF) and Interacting Multiple Model(IMM) algorithm and find that STF is a parameter-adaptive algorithm and IMM is a model-adaptive algorithm. It means that they may be combined effectively. Secondly we propose a new method based on the Least-Squared Estimation to search for the fading factor in STF. After that, we design a Strong-Tracking Multiple Model Estimator (STMME) by combining the new STF with IMM. Finally, the simulation show that STMME greatly improves accuracy of velocity and acceleration compared with the conventional IMM when tracking the maneuvering target. And the computation burden increase only 6%.

AB - Firstly we analyse the properties of Strong Tracking Filter (STF) and Interacting Multiple Model(IMM) algorithm and find that STF is a parameter-adaptive algorithm and IMM is a model-adaptive algorithm. It means that they may be combined effectively. Secondly we propose a new method based on the Least-Squared Estimation to search for the fading factor in STF. After that, we design a Strong-Tracking Multiple Model Estimator (STMME) by combining the new STF with IMM. Finally, the simulation show that STMME greatly improves accuracy of velocity and acceleration compared with the conventional IMM when tracking the maneuvering target. And the computation burden increase only 6%.

KW - Fault detection

KW - Interacting multiple model algorithm

KW - Strong tracking filter

KW - Tracking maneuvering targets

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M3 - 文章

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JO - Tien Tzu Hsueh Pao/Acta Electronica Sinica

JF - Tien Tzu Hsueh Pao/Acta Electronica Sinica

IS - 1

ER -

Strong-tracking multiple model estimator

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Keywords

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