Scaled UKF with reduced sigma points for initial alignment of SINS

Yuliang Mao; Jiabin Chen; Chunlei Song; Weisheng Wu

Scaled UKF with reduced sigma points for initial alignment of SINS

Yuliang Mao^*, Jiabin Chen, Chunlei Song, Weisheng Wu

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

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

7 Citations (Scopus)

Abstract

The error model of the initial alignment of strapdown inertial navigation system (SINS) is nonlinear when the azimuth angle error is large. As the dimension of the system increases, the computation of the sigma points needed by UKF becomes burdensome, and the sigma points are no longer local sampling points. These non-local sigma points can't represent the system state correctly, and are prone to causing estimate error. In this paper, an improved filtering method combing the reduced sigma points UKF and the scaled UKF is proposed and implemented for initial alignment of SINS. The experiment results show that it yields better performance than EKF.

Original language	English
Title of host publication	Proceedings of the 30th Chinese Control Conference, CCC 2011
Pages	106-110
Number of pages	5
Publication status	Published - 2011
Event	30th Chinese Control Conference, CCC 2011 - Yantai, China Duration: 22 Jul 2011 → 24 Jul 2011

Publication series

Name	Proceedings of the 30th Chinese Control Conference, CCC 2011

Conference

Conference	30th Chinese Control Conference, CCC 2011
Country/Territory	China
City	Yantai
Period	22/07/11 → 24/07/11

Keywords

SINS
Sigma point
UKF

Cite this

@inproceedings{e68d281333b1407985c0f4b21ae46f39,

title = "Scaled UKF with reduced sigma points for initial alignment of SINS",

abstract = "The error model of the initial alignment of strapdown inertial navigation system (SINS) is nonlinear when the azimuth angle error is large. As the dimension of the system increases, the computation of the sigma points needed by UKF becomes burdensome, and the sigma points are no longer local sampling points. These non-local sigma points can't represent the system state correctly, and are prone to causing estimate error. In this paper, an improved filtering method combing the reduced sigma points UKF and the scaled UKF is proposed and implemented for initial alignment of SINS. The experiment results show that it yields better performance than EKF.",

keywords = "SINS, Sigma point, UKF",

author = "Yuliang Mao and Jiabin Chen and Chunlei Song and Weisheng Wu",

year = "2011",

language = "English",

isbn = "9789881725592",

series = "Proceedings of the 30th Chinese Control Conference, CCC 2011",

pages = "106--110",

booktitle = "Proceedings of the 30th Chinese Control Conference, CCC 2011",

note = "30th Chinese Control Conference, CCC 2011 ; Conference date: 22-07-2011 Through 24-07-2011",

}

Scaled UKF with reduced sigma points for initial alignment of SINS. / Mao, Yuliang; Chen, Jiabin ; Song, Chunlei et al.
Proceedings of the 30th Chinese Control Conference, CCC 2011. 2011. p. 106-110 6000749 (Proceedings of the 30th Chinese Control Conference, CCC 2011).

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

TY - GEN

T1 - Scaled UKF with reduced sigma points for initial alignment of SINS

AU - Mao, Yuliang

AU - Chen, Jiabin

AU - Song, Chunlei

AU - Wu, Weisheng

PY - 2011

Y1 - 2011

N2 - The error model of the initial alignment of strapdown inertial navigation system (SINS) is nonlinear when the azimuth angle error is large. As the dimension of the system increases, the computation of the sigma points needed by UKF becomes burdensome, and the sigma points are no longer local sampling points. These non-local sigma points can't represent the system state correctly, and are prone to causing estimate error. In this paper, an improved filtering method combing the reduced sigma points UKF and the scaled UKF is proposed and implemented for initial alignment of SINS. The experiment results show that it yields better performance than EKF.

AB - The error model of the initial alignment of strapdown inertial navigation system (SINS) is nonlinear when the azimuth angle error is large. As the dimension of the system increases, the computation of the sigma points needed by UKF becomes burdensome, and the sigma points are no longer local sampling points. These non-local sigma points can't represent the system state correctly, and are prone to causing estimate error. In this paper, an improved filtering method combing the reduced sigma points UKF and the scaled UKF is proposed and implemented for initial alignment of SINS. The experiment results show that it yields better performance than EKF.

KW - SINS

KW - Sigma point

KW - UKF

UR - http://www.scopus.com/inward/record.url?scp=80053090669&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:80053090669

SN - 9789881725592

T3 - Proceedings of the 30th Chinese Control Conference, CCC 2011

SP - 106

EP - 110

BT - Proceedings of the 30th Chinese Control Conference, CCC 2011

T2 - 30th Chinese Control Conference, CCC 2011

Y2 - 22 July 2011 through 24 July 2011

ER -

Scaled UKF with reduced sigma points for initial alignment of SINS

Abstract

Publication series

Conference

Keywords

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