A novel robust MM filter for target tracking with glints

Yong Liu; Yan Liang; Quan Pan

A novel robust MM filter for target tracking with glints

Yong Liu, Yan Liang, Quan Pan

School of Automation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Interacting Multiple Model (IMM) filter faces significant outlier-caused peak-errors. In this paper, the Bayesian probability update in IMM is found equivalent to Dempster's Rule of Combination which cannot handle evidence conflicts caused by outliers. Furthermore, a novel robust MM (RMM) filter is proposed through introducing expert rules about mode evolvement and presenting the Likelihood Temporal Ratio (LTR) and building the Induced Combination Rule (ICR). Simulations about target tracking show the effectiveness of the proposed method.

Original language	English
Title of host publication	Proceedings of the 32nd Chinese Control Conference, CCC 2013
Publisher	IEEE Computer Society
Pages	4793-4798
Number of pages	6
ISBN (Print)	9789881563835
State	Published - 18 Oct 2013
Event	32nd Chinese Control Conference, CCC 2013 - Xi'an, China Duration: 26 Jul 2013 → 28 Jul 2013

Publication series

Name	Chinese Control Conference, CCC
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	32nd Chinese Control Conference, CCC 2013
Country/Territory	China
City	Xi'an
Period	26/07/13 → 28/07/13

Keywords

Dempster-Shafer Theory
Interacting Multiple Model
Non-Gaussian Noise
Outlier
Robust Filter

Cite this

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title = "A novel robust MM filter for target tracking with glints",

abstract = "Interacting Multiple Model (IMM) filter faces significant outlier-caused peak-errors. In this paper, the Bayesian probability update in IMM is found equivalent to Dempster's Rule of Combination which cannot handle evidence conflicts caused by outliers. Furthermore, a novel robust MM (RMM) filter is proposed through introducing expert rules about mode evolvement and presenting the Likelihood Temporal Ratio (LTR) and building the Induced Combination Rule (ICR). Simulations about target tracking show the effectiveness of the proposed method.",

keywords = "Dempster-Shafer Theory, Interacting Multiple Model, Non-Gaussian Noise, Outlier, Robust Filter",

author = "Yong Liu and Yan Liang and Quan Pan",

year = "2013",

month = oct,

day = "18",

language = "英语",

isbn = "9789881563835",

series = "Chinese Control Conference, CCC",

publisher = "IEEE Computer Society",

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note = "32nd Chinese Control Conference, CCC 2013 ; Conference date: 26-07-2013 Through 28-07-2013",

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AU - Liang, Yan

AU - Pan, Quan

PY - 2013/10/18

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N2 - Interacting Multiple Model (IMM) filter faces significant outlier-caused peak-errors. In this paper, the Bayesian probability update in IMM is found equivalent to Dempster's Rule of Combination which cannot handle evidence conflicts caused by outliers. Furthermore, a novel robust MM (RMM) filter is proposed through introducing expert rules about mode evolvement and presenting the Likelihood Temporal Ratio (LTR) and building the Induced Combination Rule (ICR). Simulations about target tracking show the effectiveness of the proposed method.

AB - Interacting Multiple Model (IMM) filter faces significant outlier-caused peak-errors. In this paper, the Bayesian probability update in IMM is found equivalent to Dempster's Rule of Combination which cannot handle evidence conflicts caused by outliers. Furthermore, a novel robust MM (RMM) filter is proposed through introducing expert rules about mode evolvement and presenting the Likelihood Temporal Ratio (LTR) and building the Induced Combination Rule (ICR). Simulations about target tracking show the effectiveness of the proposed method.

KW - Dempster-Shafer Theory

KW - Interacting Multiple Model

KW - Non-Gaussian Noise

KW - Outlier

KW - Robust Filter

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M3 - 会议稿件

AN - SCOPUS:84890533684

SN - 9789881563835

T3 - Chinese Control Conference, CCC

SP - 4793

EP - 4798

BT - Proceedings of the 32nd Chinese Control Conference, CCC 2013

PB - IEEE Computer Society

T2 - 32nd Chinese Control Conference, CCC 2013

Y2 - 26 July 2013 through 28 July 2013

ER -

A novel robust MM filter for target tracking with glints

Abstract

Publication series

Conference

Keywords

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