Research of the Improved Kalman Filtering Algorithm on How to Accelerate the Convergence Speed of GPS Positioning

Guoliang Sun; Liu Yang

doi:10.1109/ICCT50939.2020.9295808

Research of the Improved Kalman Filtering Algorithm on How to Accelerate the Convergence Speed of GPS Positioning

Guoliang Sun
, Liu Yang

School of Electronic and Information Engineering

Beihang University

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

Abstract

Based on the characteristics of the Kalman filtering algorithm and least-squares algorithm based on Tikhonov regularization method, an improved Kalman filtering algorithm is designed to accelerate the convergence speed of GPS positioning. In the initial short epochs, the least-squares algorithm based on Tikhonov regularization method is used to obtain the floating point solution and its corresponding covariance matrix, which are used to assist the Kalman filtering to accelerate the convergence speed. Through computer simulation and actual test data analysis, the improved method proposed in the paper has a faster convergence speed compared with the traditional Kalman filtering algorithm.

Original language	English
Title of host publication	2020 IEEE 20th International Conference on Communication Technology, ICCT 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	543-546
Number of pages	4
ISBN (Electronic)	9781728181417
DOIs	https://doi.org/10.1109/ICCT50939.2020.9295808
State	Published - 28 Oct 2020
Event	20th IEEE International Conference on Communication Technology, ICCT 2020 - Nanning, China Duration: 28 Oct 2020 → 31 Oct 2020

Publication series

Name	International Conference on Communication Technology Proceedings, ICCT
Volume	2020-October

Conference

Conference	20th IEEE International Conference on Communication Technology, ICCT 2020
Country/Territory	China
City	Nanning
Period	28/10/20 → 31/10/20

Keywords

Kalman filtering
Tikhonov regularization
the convergence speed

Access to Document

10.1109/ICCT50939.2020.9295808

Cite this

Sun, G., & Yang, L. (2020). Research of the Improved Kalman Filtering Algorithm on How to Accelerate the Convergence Speed of GPS Positioning. In 2020 IEEE 20th International Conference on Communication Technology, ICCT 2020 (pp. 543-546). Article 9295808 (International Conference on Communication Technology Proceedings, ICCT; Vol. 2020-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCT50939.2020.9295808

Sun, Guoliang ; Yang, Liu. / Research of the Improved Kalman Filtering Algorithm on How to Accelerate the Convergence Speed of GPS Positioning. 2020 IEEE 20th International Conference on Communication Technology, ICCT 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 543-546 (International Conference on Communication Technology Proceedings, ICCT).

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title = "Research of the Improved Kalman Filtering Algorithm on How to Accelerate the Convergence Speed of GPS Positioning",

abstract = "Based on the characteristics of the Kalman filtering algorithm and least-squares algorithm based on Tikhonov regularization method, an improved Kalman filtering algorithm is designed to accelerate the convergence speed of GPS positioning. In the initial short epochs, the least-squares algorithm based on Tikhonov regularization method is used to obtain the floating point solution and its corresponding covariance matrix, which are used to assist the Kalman filtering to accelerate the convergence speed. Through computer simulation and actual test data analysis, the improved method proposed in the paper has a faster convergence speed compared with the traditional Kalman filtering algorithm.",

keywords = "Kalman filtering, Tikhonov regularization, the convergence speed",

author = "Guoliang Sun and Liu Yang",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 20th IEEE International Conference on Communication Technology, ICCT 2020 ; Conference date: 28-10-2020 Through 31-10-2020",

year = "2020",

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doi = "10.1109/ICCT50939.2020.9295808",

language = "英语",

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Sun, G & Yang, L 2020, Research of the Improved Kalman Filtering Algorithm on How to Accelerate the Convergence Speed of GPS Positioning. in 2020 IEEE 20th International Conference on Communication Technology, ICCT 2020., 9295808, International Conference on Communication Technology Proceedings, ICCT, vol. 2020-October, Institute of Electrical and Electronics Engineers Inc., pp. 543-546, 20th IEEE International Conference on Communication Technology, ICCT 2020, Nanning, China, 28/10/20. https://doi.org/10.1109/ICCT50939.2020.9295808

Research of the Improved Kalman Filtering Algorithm on How to Accelerate the Convergence Speed of GPS Positioning. / Sun, Guoliang; Yang, Liu.
2020 IEEE 20th International Conference on Communication Technology, ICCT 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 543-546 9295808 (International Conference on Communication Technology Proceedings, ICCT; Vol. 2020-October).

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

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AU - Sun, Guoliang

AU - Yang, Liu

PY - 2020/10/28

Y1 - 2020/10/28

N2 - Based on the characteristics of the Kalman filtering algorithm and least-squares algorithm based on Tikhonov regularization method, an improved Kalman filtering algorithm is designed to accelerate the convergence speed of GPS positioning. In the initial short epochs, the least-squares algorithm based on Tikhonov regularization method is used to obtain the floating point solution and its corresponding covariance matrix, which are used to assist the Kalman filtering to accelerate the convergence speed. Through computer simulation and actual test data analysis, the improved method proposed in the paper has a faster convergence speed compared with the traditional Kalman filtering algorithm.

AB - Based on the characteristics of the Kalman filtering algorithm and least-squares algorithm based on Tikhonov regularization method, an improved Kalman filtering algorithm is designed to accelerate the convergence speed of GPS positioning. In the initial short epochs, the least-squares algorithm based on Tikhonov regularization method is used to obtain the floating point solution and its corresponding covariance matrix, which are used to assist the Kalman filtering to accelerate the convergence speed. Through computer simulation and actual test data analysis, the improved method proposed in the paper has a faster convergence speed compared with the traditional Kalman filtering algorithm.

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KW - Tikhonov regularization

KW - the convergence speed

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BT - 2020 IEEE 20th International Conference on Communication Technology, ICCT 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 20th IEEE International Conference on Communication Technology, ICCT 2020

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ER -

Sun G, Yang L. Research of the Improved Kalman Filtering Algorithm on How to Accelerate the Convergence Speed of GPS Positioning. In 2020 IEEE 20th International Conference on Communication Technology, ICCT 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 543-546. 9295808. (International Conference on Communication Technology Proceedings, ICCT). doi: 10.1109/ICCT50939.2020.9295808

Research of the Improved Kalman Filtering Algorithm on How to Accelerate the Convergence Speed of GPS Positioning

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