The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system

Dongyang Zhang; Zhihong Deng; Bo Wang; Mengyin Fu

doi:10.1109/CGNCC.2016.7829155

The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system

Dongyang Zhang^*, Zhihong Deng, Bo Wang, Mengyin Fu

^*Corresponding author for this work

School of Automation

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

8 Citations (Scopus)

Abstract

The integrated navigation system can improve the navigation accuracy utilizing the redundant information. The Extended Kalman Filter (EKF) is commonly used in the integrated navigation system. It usually takes only one-order of Taylor expansion and needs to calculate the Jacobian matrix, which will affect the accuracy and numerical stability of the system significantly. Thus in this paper the application of Square-Root Cubature Kalman Filter(SCKF) method was proposed to solve the above problems in the SINS/CNS integrated navigation system. The simulation results show that the position, velocity and attitude errors are reduced effectively compared with the EKF method. The SCKF method is more suitable for the state estimation problems in integrated navigation system.

Original language	English
Title of host publication	CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2331-2335
Number of pages	5
ISBN (Electronic)	9781467383189
DOIs	https://doi.org/10.1109/CGNCC.2016.7829155
Publication status	Published - 20 Jan 2017
Event	7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016 - Nanjing, Jiangsu, China Duration: 12 Aug 2016 → 14 Aug 2016

Publication series

Name	CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

Conference

Conference	7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
Country/Territory	China
City	Nanjing, Jiangsu
Period	12/08/16 → 14/08/16

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10.1109/CGNCC.2016.7829155

Cite this

Zhang, D., Deng, Z., Wang, B., & Fu, M. (2017). The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system. In CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference (pp. 2331-2335). Article 7829155 (CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CGNCC.2016.7829155

Zhang, Dongyang ; Deng, Zhihong ; Wang, Bo et al. / The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system. CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 2331-2335 (CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference).

@inproceedings{db7117e4a49344668c28c1f41ea0d79e,

title = "The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system",

abstract = "The integrated navigation system can improve the navigation accuracy utilizing the redundant information. The Extended Kalman Filter (EKF) is commonly used in the integrated navigation system. It usually takes only one-order of Taylor expansion and needs to calculate the Jacobian matrix, which will affect the accuracy and numerical stability of the system significantly. Thus in this paper the application of Square-Root Cubature Kalman Filter(SCKF) method was proposed to solve the above problems in the SINS/CNS integrated navigation system. The simulation results show that the position, velocity and attitude errors are reduced effectively compared with the EKF method. The SCKF method is more suitable for the state estimation problems in integrated navigation system.",

author = "Dongyang Zhang and Zhihong Deng and Bo Wang and Mengyin Fu",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016 ; Conference date: 12-08-2016 Through 14-08-2016",

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Zhang, D, Deng, Z , Wang, B & Fu, M 2017, The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system. in CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference., 7829155, CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference, Institute of Electrical and Electronics Engineers Inc., pp. 2331-2335, 7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016, Nanjing, Jiangsu, China, 12/08/16. https://doi.org/10.1109/CGNCC.2016.7829155

The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system. / Zhang, Dongyang; Deng, Zhihong ; Wang, Bo et al.
CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference. Institute of Electrical and Electronics Engineers Inc., 2017. p. 2331-2335 7829155 (CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference).

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

TY - GEN

T1 - The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system

AU - Zhang, Dongyang

AU - Deng, Zhihong

AU - Wang, Bo

AU - Fu, Mengyin

PY - 2017/1/20

Y1 - 2017/1/20

N2 - The integrated navigation system can improve the navigation accuracy utilizing the redundant information. The Extended Kalman Filter (EKF) is commonly used in the integrated navigation system. It usually takes only one-order of Taylor expansion and needs to calculate the Jacobian matrix, which will affect the accuracy and numerical stability of the system significantly. Thus in this paper the application of Square-Root Cubature Kalman Filter(SCKF) method was proposed to solve the above problems in the SINS/CNS integrated navigation system. The simulation results show that the position, velocity and attitude errors are reduced effectively compared with the EKF method. The SCKF method is more suitable for the state estimation problems in integrated navigation system.

AB - The integrated navigation system can improve the navigation accuracy utilizing the redundant information. The Extended Kalman Filter (EKF) is commonly used in the integrated navigation system. It usually takes only one-order of Taylor expansion and needs to calculate the Jacobian matrix, which will affect the accuracy and numerical stability of the system significantly. Thus in this paper the application of Square-Root Cubature Kalman Filter(SCKF) method was proposed to solve the above problems in the SINS/CNS integrated navigation system. The simulation results show that the position, velocity and attitude errors are reduced effectively compared with the EKF method. The SCKF method is more suitable for the state estimation problems in integrated navigation system.

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M3 - Conference contribution

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T3 - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

SP - 2331

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BT - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

PB - Institute of Electrical and Electronics Engineers Inc.

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Zhang D, Deng Z , Wang B, Fu M. The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system. In CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference. Institute of Electrical and Electronics Engineers Inc. 2017. p. 2331-2335. 7829155. (CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference). doi: 10.1109/CGNCC.2016.7829155

The application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system

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