A Self-Calibration Method for Non-Orthogonal Angles of Gimbals in Tri-Axis Rotational Inertial Navigation System

Gao, Pengyu; Li, Kui; Wang, Lei; Gao, Jiaxin

doi:10.1109/jsen.2016.2616356

Cited by 61 publications

(25 citation statements)

References 18 publications

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“…Meanwhile, proper rotation scheme design can help modulate and estimate error parameters of IMU. Taking commercial cost into consideration, triaxis and dual-axis RINSs are more expensive than single-axis [15][16][17][18]. In consequence, single-axis RINS will be mainly discussed in this paper.…”

Section: Introductionmentioning

confidence: 99%

Error Mechanism and Self‐Calibration of Single‐Axis Rotational Inertial Navigation System

Nie

Chen

Luo

et al. 2019

Mathematical Problems in Engineering

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With the rapid development of inertial technology, the rotational inertial system has been widely used for high-accuracy navigation. In addition, the single-axis rotational inertial navigation system is one of the most popular navigation systems due to its low cost. However, the fact which cannot be ignored is that although single axis rotational inertial navigation system can restrain divergence of attitude error, it cannot eliminate velocity error, which is mainly caused by the gyro misalignment and scale factor error related to rotational axis. A novel calibration method established on filter has been proposed. Position, velocity, and attitude are chosen to be the state variables. In order to estimate the gyro errors related to rotational axis, these errors must be included in the state equation. Correspondingly, zero velocity and rate of turntable are chosen to be measured. Simulation has been carried out to verify the correctness of the theory, and the real test has been performed to further demonstrate the validity of the method. By compensating the main error estimated by filter, it can be found that the accumulated errors in velocity and attitude are decreased. So, the precision of navigation is greatly improved with the proposed method.

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Section: Introductionmentioning

confidence: 99%

Error Mechanism and Self‐Calibration of Single‐Axis Rotational Inertial Navigation System

Nie

Chen

Luo

et al. 2019

Mathematical Problems in Engineering

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“…It takes two steps to calibrate all the parameters, firstly the IMU errors are calibrated and compensated, then the mounting errors are estimated. In reference [ 23 ], a new self-calibration method for non-orthogonal angles in the tri-axis RINS is proposed.…”

Section: Introductionmentioning

confidence: 99%

A Separated Calibration Method for Inertial Measurement Units Mounted on Three-Axis Turntables

Dong

Ren

Chen

et al. 2018

Sensors

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Inertial Measurement Unit (IMU) calibration accuracy is easily affected by turntable errors, so the primary aim of this study is to reduce the dependence on the turntable’s precision during the calibration process. Firstly, the indicated-output of the IMU considering turntable errors is constructed and with the introduction of turntable errors, the functional relationship between turntable errors and the indicated-output was derived. Then, based on a D-suboptimal design, a calibration method for simultaneously identifying the IMU error model parameters and the turntable errors was proposed. Simulation results showed that some turntable errors could thus be effectively calibrated and automatically compensated. Finally, the theoretical validity was verified through experiments. Compared with the traditional method, the method proposed in this paper can significantly reduce the influence of the turntable errors on the IMU calibration accuracy.

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“…An 8-position discontinuous rotation scheme is proposed in [ 12 , 13 ]. With respect to the rotation axis, the RINS can be divided into single-axis RINS, dual-axis RINS and triple-axis RINS [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. The differences between single-axis RINS and dual-axis RINS are studied in [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

“…With respect to the rotation axis, the RINS can be divided into single-axis RINS, dual-axis RINS and triple-axis RINS [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. The differences between single-axis RINS and dual-axis RINS are studied in [ 15 ]. The former cannot modulate the biases of the inertial sensor with the input axis coinciding with the rotation axis and the later can modulate the constant errors of all sensors by the appropriate rotation scheme [ 12 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

“…The error sources include the calibration factor error of the gyroscope, misalignment an gles of the gyroscope, misalignment angles of the accelerometer, inner level-arm error, non-orthogonal angles of gimbals, etc. There are some papers about these error sources, and appropriate calibration and compensation methods are proposed to reduce the impact of these errors and improve navigation accuracy [ 1 , 15 , 16 , 17 , 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

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Analysis and Self-Calibration Method for Asynchrony between Sensors in Rotation INS

Sui

Wang

Huang

et al. 2018

Sensors

Self Cite

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The gyroscope, accelerometer and angular encoder are the most important components in a dual-axis rotation inertial navigation system (RINS). However, there are asynchronies among the sensors, which will thus lead to navigation errors. The impact of asynchrony between the gyroscope and angular encoder on the azimuth error and the impact of asynchrony between the gyroscope and accelerometer on the velocity error are analyzed in this paper. A self-calibration method based on navigation errors is proposed based on the analysis above. Experiments show that azimuth and velocity accuracy can be improved by compensating the asynchronies.

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A Self-Calibration Method for Non-Orthogonal Angles of Gimbals in Tri-Axis Rotational Inertial Navigation System

Cited by 61 publications

References 18 publications

Error Mechanism and Self‐Calibration of Single‐Axis Rotational Inertial Navigation System

Error Mechanism and Self‐Calibration of Single‐Axis Rotational Inertial Navigation System

A Separated Calibration Method for Inertial Measurement Units Mounted on Three-Axis Turntables

Analysis and Self-Calibration Method for Asynchrony between Sensors in Rotation INS

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