Implementation of multiple-model multi-Bernoulli filter for nonlinear models

Tongyang Jiang; Meiqin Liu; Senlin Zhang

doi:10.13245/j.hust.150902

Implementation of multiple-model multi-Bernoulli filter for nonlinear models

Tongyang Jiang
, Meiqin Liu
, Senlin Zhang

Zhejiang University

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

1 Scopus citations

Abstract

Two implementations of the multiple-model multi-Bernoulli (MM-MB) filter were proposed for nonlinear system models in the presence of clutter and missed detection. Based on the cubature Kalman filtering algorithm, the cubature Kalman Gaussian mixture (CK-GM) implementation of the MM-MB filter was proposed. Moreover, to improve the numerical stability of the CK-GM-MM-MB filtering algorithm, the square-root CK-GM implementation of the MM-MB filter was proposed. Finally, a numerical example was presented to verify the effectiveness of the proposed approaches.

Original language	English
Pages (from-to)	7-12 and 18
Journal	Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition)
Volume	43
Issue number	9
DOIs	https://doi.org/10.13245/j.hust.150902
State	Published - 23 Sep 2015
Externally published	Yes

Keywords

Cubature Kalman
Gaussian mixture
Maneuvering targets
Multiple-model multi-Bernoulli filter
Nonlinear models

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10.13245/j.hust.150902

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title = "Implementation of multiple-model multi-Bernoulli filter for nonlinear models",

abstract = "Two implementations of the multiple-model multi-Bernoulli (MM-MB) filter were proposed for nonlinear system models in the presence of clutter and missed detection. Based on the cubature Kalman filtering algorithm, the cubature Kalman Gaussian mixture (CK-GM) implementation of the MM-MB filter was proposed. Moreover, to improve the numerical stability of the CK-GM-MM-MB filtering algorithm, the square-root CK-GM implementation of the MM-MB filter was proposed. Finally, a numerical example was presented to verify the effectiveness of the proposed approaches.",

keywords = "Cubature Kalman, Gaussian mixture, Maneuvering targets, Multiple-model multi-Bernoulli filter, Nonlinear models",

author = "Tongyang Jiang and Meiqin Liu and Senlin Zhang",

year = "2015",

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doi = "10.13245/j.hust.150902",

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T1 - Implementation of multiple-model multi-Bernoulli filter for nonlinear models

AU - Jiang, Tongyang

AU - Liu, Meiqin

AU - Zhang, Senlin

PY - 2015/9/23

Y1 - 2015/9/23

N2 - Two implementations of the multiple-model multi-Bernoulli (MM-MB) filter were proposed for nonlinear system models in the presence of clutter and missed detection. Based on the cubature Kalman filtering algorithm, the cubature Kalman Gaussian mixture (CK-GM) implementation of the MM-MB filter was proposed. Moreover, to improve the numerical stability of the CK-GM-MM-MB filtering algorithm, the square-root CK-GM implementation of the MM-MB filter was proposed. Finally, a numerical example was presented to verify the effectiveness of the proposed approaches.

AB - Two implementations of the multiple-model multi-Bernoulli (MM-MB) filter were proposed for nonlinear system models in the presence of clutter and missed detection. Based on the cubature Kalman filtering algorithm, the cubature Kalman Gaussian mixture (CK-GM) implementation of the MM-MB filter was proposed. Moreover, to improve the numerical stability of the CK-GM-MM-MB filtering algorithm, the square-root CK-GM implementation of the MM-MB filter was proposed. Finally, a numerical example was presented to verify the effectiveness of the proposed approaches.

KW - Cubature Kalman

KW - Gaussian mixture

KW - Maneuvering targets

KW - Multiple-model multi-Bernoulli filter

KW - Nonlinear models

UR - https://www.scopus.com/pages/publications/84945294979

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DO - 10.13245/j.hust.150902

M3 - 文章

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SN - 1671-4512

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SP - 7-12 and 18

JO - Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition)

JF - Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition)

IS - 9

ER -

Implementation of multiple-model multi-Bernoulli filter for nonlinear models

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Keywords

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