Interacting multiple models algorithm based on α-β & α-β-γ filters

Yan Liang; Quan Pan; Hongcai Zhang

Interacting multiple models algorithm based on α-β & α-β-γ filters

Yan Liang
, Quan Pan
, Hongcai Zhang

自动化学院

Northwestern Polytechnical University Xian

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

In this paper, we firstly prove in interacting multiple models algorithm (IMM) model-conditional estimational variances can be decoupled with model-conditional state estimation under certain conditions, and then supply the conditions to partly-decoupling and absolutely-decoupling among model-conditional estimational variances. Therefore IMM based on α-β α-β-γ filters is proposed. The Monte Carlo simulations show that this algorithm not only remains almost as accurate as IMM, but also save about half of the computation.

源语言	英语
期刊	Kongzhi Lilun Yu Yingyong/Control Theory and Applications
卷	16
期	5
出版状态	已出版 - 1999

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title = "Interacting multiple models algorithm based on α-β \& α-β-γ filters",

abstract = "In this paper, we firstly prove in interacting multiple models algorithm (IMM) model-conditional estimational variances can be decoupled with model-conditional state estimation under certain conditions, and then supply the conditions to partly-decoupling and absolutely-decoupling among model-conditional estimational variances. Therefore IMM based on α-β α-β-γ filters is proposed. The Monte Carlo simulations show that this algorithm not only remains almost as accurate as IMM, but also save about half of the computation.",

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AU - Pan, Quan

AU - Zhang, Hongcai

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N2 - In this paper, we firstly prove in interacting multiple models algorithm (IMM) model-conditional estimational variances can be decoupled with model-conditional state estimation under certain conditions, and then supply the conditions to partly-decoupling and absolutely-decoupling among model-conditional estimational variances. Therefore IMM based on α-β α-β-γ filters is proposed. The Monte Carlo simulations show that this algorithm not only remains almost as accurate as IMM, but also save about half of the computation.

AB - In this paper, we firstly prove in interacting multiple models algorithm (IMM) model-conditional estimational variances can be decoupled with model-conditional state estimation under certain conditions, and then supply the conditions to partly-decoupling and absolutely-decoupling among model-conditional estimational variances. Therefore IMM based on α-β α-β-γ filters is proposed. The Monte Carlo simulations show that this algorithm not only remains almost as accurate as IMM, but also save about half of the computation.

KW - α-β filter

KW - α-β-γ filter

KW - Adaptive filtering

KW - Tracking

UR - https://www.scopus.com/pages/publications/76549114722

M3 - 文章

AN - SCOPUS:76549114722

SN - 1000-8152

VL - 16

JO - Kongzhi Lilun Yu Yingyong/Control Theory and Applications

JF - Kongzhi Lilun Yu Yingyong/Control Theory and Applications

IS - 5

ER -

Interacting multiple models algorithm based on α-β & α-β-γ filters

摘要

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