Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/212953
Title: Kalman-Filtering-Based In-Motion Coarse Alignment for Odometer-Aided SINS
Authors: Yulong Huang;Yonggang Zhang;Xiaodong Wang
Year: 2017
Publisher: IEEE
Abstract: In this paper, the in-motion coarse alignment (IMCA) for odometer-aided strap-down inertial navigation system (SINS) is investigated with the main focus on compensating for the dynamic errors of gyroscope induced by severe maneuvering. A new Kalman-filtering-based IMCA method for an odometer-aided SINS is presented. A novel closed-loop approach to estimating the attitude matrix from the current body frame to the initial body frame is proposed, in which the attitude error between the closed-loop calculation and the true attitude matrix is first estimated, and then, the estimated attitude matrix is obtained by refining the closed-loop calculation with the estimated attitude error. A linear state-space model for the attitude error is derived, and then, a Kalman filter is employed to track the attitude error. Experimental results illustrate that the proposed closed-loop approach can estimate the attitude matrix from the current body frame to the initial body frame better than the existing open-loop approach, which results in improved alignment accuracy as compared with the existing optimization-based alignment method for the odometer-aided SINS when the vehicle maneuvers severely.
URI: http://localhost/handle/Hannan/212953
volume: 66
issue: 12
More Information: 3364,
3377
Appears in Collections:2017

Files in This Item:
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8016433.pdf4.09 MBAdobe PDF
Title: Kalman-Filtering-Based In-Motion Coarse Alignment for Odometer-Aided SINS
Authors: Yulong Huang;Yonggang Zhang;Xiaodong Wang
Year: 2017
Publisher: IEEE
Abstract: In this paper, the in-motion coarse alignment (IMCA) for odometer-aided strap-down inertial navigation system (SINS) is investigated with the main focus on compensating for the dynamic errors of gyroscope induced by severe maneuvering. A new Kalman-filtering-based IMCA method for an odometer-aided SINS is presented. A novel closed-loop approach to estimating the attitude matrix from the current body frame to the initial body frame is proposed, in which the attitude error between the closed-loop calculation and the true attitude matrix is first estimated, and then, the estimated attitude matrix is obtained by refining the closed-loop calculation with the estimated attitude error. A linear state-space model for the attitude error is derived, and then, a Kalman filter is employed to track the attitude error. Experimental results illustrate that the proposed closed-loop approach can estimate the attitude matrix from the current body frame to the initial body frame better than the existing open-loop approach, which results in improved alignment accuracy as compared with the existing optimization-based alignment method for the odometer-aided SINS when the vehicle maneuvers severely.
URI: http://localhost/handle/Hannan/212953
volume: 66
issue: 12
More Information: 3364,
3377
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8016433.pdf4.09 MBAdobe PDF
Title: Kalman-Filtering-Based In-Motion Coarse Alignment for Odometer-Aided SINS
Authors: Yulong Huang;Yonggang Zhang;Xiaodong Wang
Year: 2017
Publisher: IEEE
Abstract: In this paper, the in-motion coarse alignment (IMCA) for odometer-aided strap-down inertial navigation system (SINS) is investigated with the main focus on compensating for the dynamic errors of gyroscope induced by severe maneuvering. A new Kalman-filtering-based IMCA method for an odometer-aided SINS is presented. A novel closed-loop approach to estimating the attitude matrix from the current body frame to the initial body frame is proposed, in which the attitude error between the closed-loop calculation and the true attitude matrix is first estimated, and then, the estimated attitude matrix is obtained by refining the closed-loop calculation with the estimated attitude error. A linear state-space model for the attitude error is derived, and then, a Kalman filter is employed to track the attitude error. Experimental results illustrate that the proposed closed-loop approach can estimate the attitude matrix from the current body frame to the initial body frame better than the existing open-loop approach, which results in improved alignment accuracy as compared with the existing optimization-based alignment method for the odometer-aided SINS when the vehicle maneuvers severely.
URI: http://localhost/handle/Hannan/212953
volume: 66
issue: 12
More Information: 3364,
3377
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8016433.pdf4.09 MBAdobe PDF