Deterministic Particle Filter based transfer alignment method for large misalignment angle

For inertial navigation systems (INS) on moving base, transfer alignment is widely applied to initialize it. Three velocity plus attitude matching methods are compared. And Kalman filter is employed to evaluate the misalignment angle. Simulations under the same conditions show which scheme has excellent performance in precision and rapidness of estimations.

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A Transfer Alignment Method considering a Data Latency Compensation for an Inertial Navigation System in High Dynamic Applications

The Transactions of The Korean Institute of Electrical Engineers ◽

10.5370/kiee.2015.64.12.1742 ◽

2015 ◽

Vol 64 (12) ◽

pp. 1742-1747 ◽

Cited By ~ 1

Author(s):

Hyung-Sub Lee ◽

Kyung-Jun Han ◽

Sang-Woo Lee ◽

Myung-Jong Yu

Keyword(s):

Navigation System ◽

Inertial Navigation System ◽

Inertial Navigation ◽

Alignment Method ◽

Transfer Alignment ◽

High Dynamic ◽

Data Latency

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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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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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