An Improved Initial Alignment Method using Kalman Filtering of the Vectorized K-matrix

The design of an improved alignment method of SINS on a swaying base is presented in this paper. FIR filter is taken to decrease the impact caused by the lever arm effect. And the system also encompasses the online estimation of gyroscopes’ drift with Kalman filter in order to do the compensation, and the inertial freezing alignment algorithm which helps to resolve the attitude matrix with respect to its fast and robust property to provide the mathematical platform for the vehicle. Simulation results show that the proposed method is efficient for the initial alignment of the swaying base navigation system.

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Moving State Marine SINS Initial Alignment Based on High Degree CKF

Mathematical Problems in Engineering ◽

10.1155/2014/546107 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 8

Author(s):

Yong-Gang Zhang ◽

Yu-Long Huang ◽

Zhe-Min Wu ◽

Ning Li

Keyword(s):

Kalman Filter ◽

Unscented Kalman Filter ◽

Alignment Method ◽

Misalignment Angle ◽

Initial Alignment ◽

Central Difference ◽

Angle Condition ◽

Cubature Kalman Filter ◽

High Degree ◽

Central Difference Kalman Filter

A new moving state marine initial alignment method of strap-down inertial navigation system (SINS) is proposed based on high-degree cubature Kalman filter (CKF), which can capture higher order Taylor expansion terms of nonlinear alignment model than the existing third-degree CKF, unscented Kalman filter and central difference Kalman filter, and improve the accuracy of initial alignment under large heading misalignment angle condition. Simulation results show the efficiency and advantage of the proposed initial alignment method as compared with existing initial alignment methods for the moving state SINS initial alignment with large heading misalignment angle.

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Quaternion Estimation Using Kalman Filtering of the Vectorized K-Matrix

AIAA Guidance, Navigation, and Control Conference ◽

10.2514/6.2009-6310 ◽

2009 ◽

Cited By ~ 1

Author(s):

Daniel Choukroun

Keyword(s):

Kalman Filtering ◽

K Matrix

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Research on Initial Alignment Method of SINS with Improved CKF

2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) ◽

10.1109/itnec.2019.8729514 ◽

2019 ◽

Author(s):

Guoqiang Zhang ◽

Changhua Lu ◽

Yan Li

Keyword(s):

Alignment Method ◽

Initial Alignment

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A Rapid Transfer Alignment Method for SINS Based on the Added Backward-Forward SINS Resolution and Data Fusion

Mathematical Problems in Engineering ◽

10.1155/2013/401794 ◽

2013 ◽

Vol 2013 ◽

pp. 1-10 ◽

Cited By ~ 3

Author(s):

Xixiang Liu ◽

Xiaosu Xu ◽

Yiting Liu ◽

Lihui Wang

Keyword(s):

Data Fusion ◽

Reference Data ◽

Inertial Sensor ◽

Sensor Data ◽

Alignment Method ◽

Initial Alignment ◽

Transfer Alignment ◽

Gyro Bias ◽

Sensor Errors ◽

Rapid Transfer

Two viewpoints are given: (1) initial alignment of strapdown inertial navigation system (SINS) can be fulfilled with a set of inertial sensor data; (2) estimation time for sensor errors can be shortened by repeated data fusion on the added backward-forward SINS resolution results and the external reference data. Based on the above viewpoints, aiming to estimate gyro bias in a shortened time, a rapid transfer alignment method, without any changes for Kalman filter, is introduced. In this method, inertial sensor data and reference data in one reference data update cycle are stored, and one backward and one forward SINS resolutions are executed. Meanwhile, data fusion is executed when the corresponding resolution ends. With the added backward-forward SINS resolution, in the above mentioned update cycle, the estimating operations for gyro bias are added twice, and the estimation time for it is shortened. In the ship swinging condition, with the “velocity plus yaw” matching, the effectiveness of this method is proved by the simulation.

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Initial Alignment Algorithm Study Based on Rotating Modulation and Kalman Filtering

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.513-517.585 ◽

2014 ◽

Vol 513-517 ◽

pp. 585-588 ◽

Cited By ~ 1

Author(s):

Zhi Wei Zhang ◽

Hua Dong Sun

Keyword(s):

Theoretical Analysis ◽

Test Data ◽

Kalman Filtering ◽

Alignment Algorithm ◽

Environmental Disturbance ◽

Initial Alignment

Kalman filtering is used to restrain the influence of environmental disturbance to the initial alignment precision. Meanwhile, rotating modulation is utilized to reduce the influence of peg-top excursion and accelerometer zero deflection. The theoretical analysis and test data demonstrate that the proposed algorithm can improve the alignment precision by the combination of the two methods.

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