A Self-Calibration Method for the Installation Errors of Rotation Axes Based on the Asynchronous Rotation of Rotational Inertial Navigation Systems

2018 ◽  
Vol 65 (4) ◽  
pp. 3550-3558 ◽  
Author(s):  
Peida Hu ◽  
Peng Xu ◽  
Bingxu Chen ◽  
Qiuping Wu
Keyword(s):  
Inertial Navigation ◽  
Calibration Method ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Self Calibration ◽  
Rotation Axes

scholarly journals A Dynamic Calibration Method of Installation Misalignment Angles between Two Inertial Navigation Systems

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2947
Author(s):  
Ming Hua ◽  
Kui Li ◽  
Yanhong Lv ◽  
Qi Wu
Keyword(s):  
Autonomous Navigation ◽  
Inertial Navigation ◽  
Calibration Method ◽  
Measurement Information ◽  
Dynamic Calibration ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Additional Information ◽  
Two Systems ◽  
Dynamic Calibration Method

Generally, in order to ensure the reliability of Navigation system, vehicles are usually equipped with two or more sets of inertial navigation systems (INSs). Fusion of navigation measurement information from different sets of INSs can improve the accuracy of autonomous navigation effectively. However, due to the existence of misalignment angles, the coordinate axes of different systems are usually not in coincidence with each other absolutely, which would lead to serious problems when integrating the attitudes information. Therefore, it is necessary to precisely calibrate and compensate the misalignment angles between different systems. In this paper, a dynamic calibration method of misalignment angles between two systems was proposed. This method uses the speed and attitude information of two sets of INSs during the movement of the vehicle as measurements to dynamically calibrate the misalignment angles of two systems without additional information sources or other external measuring equipment, such as turntable. A mathematical model of misalignment angles between two INSs was established. The simulation experiment and the INSs vehicle experiments were conducted to verify the effectiveness of the method. The results show that the calibration accuracy of misalignment angles between the two sets of systems can reach to 1″ while using the proposed method.

A new multi-position calibration method for MEMS inertial navigation systems

2007 ◽  
Vol 18 (7) ◽  
pp. 1897-1907 ◽  
Author(s):  
Z F Syed ◽  
P Aggarwal ◽  
C Goodall ◽  
X Niu ◽  
N El-Sheimy
Keyword(s):  
Inertial Navigation ◽  
Calibration Method ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Position Calibration

scholarly journals A System-Level Self-Calibration Method for Installation Errors in A Dual-Axis Rotational Inertial Navigation System

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4005 ◽  
Author(s):  
Bai ◽  
Lai ◽  
Lyu ◽  
Xu ◽  
Liu ◽  
...  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Angular Rate ◽  
Inertial Navigation ◽  
Calibration Method ◽  
System Level ◽  
Measurement Unit ◽  
Self Calibration ◽  
Rotation Axes ◽  
Rotation Scheme

In a dual-axis rotational inertial navigation system (RINS), there are two kinds of installation errors, nonorthogonal installation errors of inertial sensors, and installation errors between the inertial measurement unit (IMU) and rotation axes. Traditionally, these two errors are not considered simultaneously. Thus, they are calibrated separately by different estimation algorithms and rotation schemes. In this paper, a system-level self-calibration method for installation errors of a dual-axis RINS is proposed. Based on the Kalman filter, the measurement model is reestablished to ensure that all installation errors can be estimated together. First, the relationship between the initial attitude and subsequent attitude of IMU during rotation is used as a constraint to estimate nonorthogonal installation errors of accelerometers, and installation errors between the IMU and rotation axes. Then, the angular rate of the rotation mechanism is used as a reference to estimate nonorthogonal installation errors of the gyros. The rotation scheme of the IMU is designed to make all installation errors observable, and the observability of the system is analyzed based on the piecewise constant system method. Simulation and laboratory experiment results suggest that installation errors can be effectively estimated by the proposed method, thereby avoiding the complex separating process.

Analysis of Three Velocity Plus Attitude Matching Methods for Transfer Alignment

2012 ◽  
Vol 433-440 ◽  
pp. 2802-2807
Author(s):  
Ying Hong Han ◽  
Wan Chun Chen
Keyword(s):  
Kalman Filter ◽  
Inertial Navigation ◽  
Navigation Systems ◽  
Misalignment Angle ◽  
Inertial Navigation Systems ◽  
Excellent Performance ◽  
Transfer Alignment ◽  
Matching Methods ◽  
Moving Base

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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