A carrier tracking algorithm of kalman filter based on combined maneuvering target model

Zhulin Xiong; Shijie Ren; Celun Liu; Jianping An

doi:10.1007/978-3-662-48386-2_29

A carrier tracking algorithm of kalman filter based on combined maneuvering target model

Zhulin Xiong, Shijie Ren, Celun Liu^*, Jianping An

^*Corresponding author for this work

School of Cyberspace Science and Technology

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

Abstract

Since the traditional current statistical Kalman (CS-Kalman) filter doesn’t perform well enough when used in high-dynamic carrier tracking, an carrier tracking algorithm of Kalman filter based on combined maneuvering target model composed of high dynamic CS-Kalman filter and steady-state self-adaptive CS-Kalman filter is presented. The proposed algorithm achieves stable and accurate carrier synchronization by adjusting the CS-Kalman filter type and parameter corresponding to the dynamic condition in real time. Simulation results show that compared with the traditional CS-Kalman algorithm, the proposed algorithm is more realistic, practical valuable and adaptable in high dynamic environment.

Original language	English
Title of host publication	Proceedings of the 2015 Chinese Intelligent Systems Conference
Editors	Hongbo Li, Weicun Zhang, Yingmin Jia, Junping Du
Publisher	Springer Verlag
Pages	273-281
Number of pages	9
ISBN (Print)	9783662483848
DOIs	https://doi.org/10.1007/978-3-662-48386-2_29
Publication status	Published - 2016
Event	Chinese Intelligent Systems Conference, CISC 2015 - Yangzhou, China Duration: 1 Jan 2015 → …

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	359
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	Chinese Intelligent Systems Conference, CISC 2015
Country/Territory	China
City	Yangzhou
Period	1/01/15 → …

Keywords

Carrier tracking
Current statistical kalman (CS-Kalman) filter
High dynamic
Maneuvering target model

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10.1007/978-3-662-48386-2_29

Cite this

Xiong, Z., Ren, S., Liu, C., & An, J. (2016). A carrier tracking algorithm of kalman filter based on combined maneuvering target model. In H. Li, W. Zhang, Y. Jia, & J. Du (Eds.), Proceedings of the 2015 Chinese Intelligent Systems Conference (pp. 273-281). (Lecture Notes in Electrical Engineering; Vol. 359). Springer Verlag. https://doi.org/10.1007/978-3-662-48386-2_29

@inproceedings{b24ead52f89243628b756a2965510e1e,

title = "A carrier tracking algorithm of kalman filter based on combined maneuvering target model",

abstract = "Since the traditional current statistical Kalman (CS-Kalman) filter doesn{\textquoteright}t perform well enough when used in high-dynamic carrier tracking, an carrier tracking algorithm of Kalman filter based on combined maneuvering target model composed of high dynamic CS-Kalman filter and steady-state self-adaptive CS-Kalman filter is presented. The proposed algorithm achieves stable and accurate carrier synchronization by adjusting the CS-Kalman filter type and parameter corresponding to the dynamic condition in real time. Simulation results show that compared with the traditional CS-Kalman algorithm, the proposed algorithm is more realistic, practical valuable and adaptable in high dynamic environment.",

keywords = "Carrier tracking, Current statistical kalman (CS-Kalman) filter, High dynamic, Maneuvering target model",

author = "Zhulin Xiong and Shijie Ren and Celun Liu and Jianping An",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2016.; Chinese Intelligent Systems Conference, CISC 2015 ; Conference date: 01-01-2015",

year = "2016",

doi = "10.1007/978-3-662-48386-2_29",

language = "English",

isbn = "9783662483848",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Verlag",

pages = "273--281",

editor = "Hongbo Li and Weicun Zhang and Yingmin Jia and Junping Du",

booktitle = "Proceedings of the 2015 Chinese Intelligent Systems Conference",

address = "Germany",

}

Xiong, Z, Ren, S, Liu, C & An, J 2016, A carrier tracking algorithm of kalman filter based on combined maneuvering target model. in H Li, W Zhang, Y Jia & J Du (eds), Proceedings of the 2015 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol. 359, Springer Verlag, pp. 273-281, Chinese Intelligent Systems Conference, CISC 2015, Yangzhou, China, 1/01/15. https://doi.org/10.1007/978-3-662-48386-2_29

A carrier tracking algorithm of kalman filter based on combined maneuvering target model. / Xiong, Zhulin; Ren, Shijie; Liu, Celun et al.
Proceedings of the 2015 Chinese Intelligent Systems Conference. ed. / Hongbo Li; Weicun Zhang; Yingmin Jia; Junping Du. Springer Verlag, 2016. p. 273-281 (Lecture Notes in Electrical Engineering; Vol. 359).

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

TY - GEN

T1 - A carrier tracking algorithm of kalman filter based on combined maneuvering target model

AU - Xiong, Zhulin

AU - Ren, Shijie

AU - Liu, Celun

AU - An, Jianping

N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2016.

PY - 2016

Y1 - 2016

N2 - Since the traditional current statistical Kalman (CS-Kalman) filter doesn’t perform well enough when used in high-dynamic carrier tracking, an carrier tracking algorithm of Kalman filter based on combined maneuvering target model composed of high dynamic CS-Kalman filter and steady-state self-adaptive CS-Kalman filter is presented. The proposed algorithm achieves stable and accurate carrier synchronization by adjusting the CS-Kalman filter type and parameter corresponding to the dynamic condition in real time. Simulation results show that compared with the traditional CS-Kalman algorithm, the proposed algorithm is more realistic, practical valuable and adaptable in high dynamic environment.

AB - Since the traditional current statistical Kalman (CS-Kalman) filter doesn’t perform well enough when used in high-dynamic carrier tracking, an carrier tracking algorithm of Kalman filter based on combined maneuvering target model composed of high dynamic CS-Kalman filter and steady-state self-adaptive CS-Kalman filter is presented. The proposed algorithm achieves stable and accurate carrier synchronization by adjusting the CS-Kalman filter type and parameter corresponding to the dynamic condition in real time. Simulation results show that compared with the traditional CS-Kalman algorithm, the proposed algorithm is more realistic, practical valuable and adaptable in high dynamic environment.

KW - Carrier tracking

KW - Current statistical kalman (CS-Kalman) filter

KW - High dynamic

KW - Maneuvering target model

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U2 - 10.1007/978-3-662-48386-2_29

DO - 10.1007/978-3-662-48386-2_29

M3 - Conference contribution

AN - SCOPUS:84952684095

SN - 9783662483848

T3 - Lecture Notes in Electrical Engineering

SP - 273

EP - 281

BT - Proceedings of the 2015 Chinese Intelligent Systems Conference

A2 - Li, Hongbo

A2 - Zhang, Weicun

A2 - Jia, Yingmin

A2 - Du, Junping

PB - Springer Verlag

T2 - Chinese Intelligent Systems Conference, CISC 2015

Y2 - 1 January 2015

ER -

A carrier tracking algorithm of kalman filter based on combined maneuvering target model

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