An adaptive Kalman filter with dynamic rescaling of process noise

Zhansheng Duan; Chongzhao Han; Hongshe Dang

doi:10.1109/ICIF.2003.177389

An adaptive Kalman filter with dynamic rescaling of process noise

Zhansheng Duan
, Chongzhao Han
, Hongshe Dang

Faculty of Electronic and Information Engineering

Xi'an Jiaotong University

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

9 Scopus citations

Abstract

In this paper; a novel adaptive Kalman filter is proposed to track maneuvering target with unknown process noise statistics. The process noise statistics are estimated by Sage's algorithm firstly; then a residual based hypothesis testing method is used to detect the likely divergence of the filter; once detected, a time- varying scale factor matrix is proposed to modify the estimated value of the process noise covariance, thus an adaptive Kalman filtering algorithm with dynamic rescaling of the process noise is derived. By using the mean-adaptive acceleration model, validity of the proposed algorithm is verified by means of Monte-Carlo simulations in two typical target maneuver scenarios.

Original language	English
Title of host publication	Proceedings of the 6th International Conference on Information Fusion, FUSION 2003
Publisher	IEEE Computer Society
Pages	1310-1315
Number of pages	6
ISBN (Print)	0972184449, 9780972184441
DOIs	https://doi.org/10.1109/ICIF.2003.177389
State	Published - 2003
Event	6th International Conference on Information Fusion, FUSION 2003 - Cairns, QLD, Australia Duration: 8 Jul 2003 → 11 Jul 2003

Publication series

Name	Proceedings of the 6th International Conference on Information Fusion, FUSION 2003
Volume	2

Conference

Conference	6th International Conference on Information Fusion, FUSION 2003
Country/Territory	Australia
City	Cairns, QLD
Period	8/07/03 → 11/07/03

Keywords

Adaptive kalman filtering
Dynamic rescaling of process noise
Maneuvering target tracking

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10.1109/ICIF.2003.177389

Cite this

Duan, Z., Han, C., & Dang, H. (2003). An adaptive Kalman filter with dynamic rescaling of process noise. In Proceedings of the 6th International Conference on Information Fusion, FUSION 2003 (pp. 1310-1315). Article 1255356 (Proceedings of the 6th International Conference on Information Fusion, FUSION 2003; Vol. 2). IEEE Computer Society. https://doi.org/10.1109/ICIF.2003.177389

@inproceedings{1e66acb4d2db47d0becc1f04d526766f,

title = "An adaptive Kalman filter with dynamic rescaling of process noise",

abstract = "In this paper; a novel adaptive Kalman filter is proposed to track maneuvering target with unknown process noise statistics. The process noise statistics are estimated by Sage's algorithm firstly; then a residual based hypothesis testing method is used to detect the likely divergence of the filter; once detected, a time- varying scale factor matrix is proposed to modify the estimated value of the process noise covariance, thus an adaptive Kalman filtering algorithm with dynamic rescaling of the process noise is derived. By using the mean-adaptive acceleration model, validity of the proposed algorithm is verified by means of Monte-Carlo simulations in two typical target maneuver scenarios.",

keywords = "Adaptive kalman filtering, Dynamic rescaling of process noise, Maneuvering target tracking",

author = "Zhansheng Duan and Chongzhao Han and Hongshe Dang",

year = "2003",

doi = "10.1109/ICIF.2003.177389",

language = "英语",

isbn = "0972184449",

series = "Proceedings of the 6th International Conference on Information Fusion, FUSION 2003",

publisher = "IEEE Computer Society",

pages = "1310--1315",

booktitle = "Proceedings of the 6th International Conference on Information Fusion, FUSION 2003",

note = "6th International Conference on Information Fusion, FUSION 2003 ; Conference date: 08-07-2003 Through 11-07-2003",

}

Duan, Z, Han, C & Dang, H 2003, An adaptive Kalman filter with dynamic rescaling of process noise. in Proceedings of the 6th International Conference on Information Fusion, FUSION 2003., 1255356, Proceedings of the 6th International Conference on Information Fusion, FUSION 2003, vol. 2, IEEE Computer Society, pp. 1310-1315, 6th International Conference on Information Fusion, FUSION 2003, Cairns, QLD, Australia, 8/07/03. https://doi.org/10.1109/ICIF.2003.177389

An adaptive Kalman filter with dynamic rescaling of process noise. / Duan, Zhansheng; Han, Chongzhao; Dang, Hongshe.
Proceedings of the 6th International Conference on Information Fusion, FUSION 2003. IEEE Computer Society, 2003. p. 1310-1315 1255356 (Proceedings of the 6th International Conference on Information Fusion, FUSION 2003; Vol. 2).

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

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AU - Duan, Zhansheng

AU - Han, Chongzhao

AU - Dang, Hongshe

PY - 2003

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N2 - In this paper; a novel adaptive Kalman filter is proposed to track maneuvering target with unknown process noise statistics. The process noise statistics are estimated by Sage's algorithm firstly; then a residual based hypothesis testing method is used to detect the likely divergence of the filter; once detected, a time- varying scale factor matrix is proposed to modify the estimated value of the process noise covariance, thus an adaptive Kalman filtering algorithm with dynamic rescaling of the process noise is derived. By using the mean-adaptive acceleration model, validity of the proposed algorithm is verified by means of Monte-Carlo simulations in two typical target maneuver scenarios.

AB - In this paper; a novel adaptive Kalman filter is proposed to track maneuvering target with unknown process noise statistics. The process noise statistics are estimated by Sage's algorithm firstly; then a residual based hypothesis testing method is used to detect the likely divergence of the filter; once detected, a time- varying scale factor matrix is proposed to modify the estimated value of the process noise covariance, thus an adaptive Kalman filtering algorithm with dynamic rescaling of the process noise is derived. By using the mean-adaptive acceleration model, validity of the proposed algorithm is verified by means of Monte-Carlo simulations in two typical target maneuver scenarios.

KW - Adaptive kalman filtering

KW - Dynamic rescaling of process noise

KW - Maneuvering target tracking

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DO - 10.1109/ICIF.2003.177389

M3 - 会议稿件

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SN - 0972184449

SN - 9780972184441

T3 - Proceedings of the 6th International Conference on Information Fusion, FUSION 2003

SP - 1310

EP - 1315

BT - Proceedings of the 6th International Conference on Information Fusion, FUSION 2003

PB - IEEE Computer Society

T2 - 6th International Conference on Information Fusion, FUSION 2003

Y2 - 8 July 2003 through 11 July 2003

ER -

An adaptive Kalman filter with dynamic rescaling of process noise

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