A high-accuracy initial alignment method based on backtracking process for strapdown inertial navigation system

Lin, Yusen; Liu, Miao; Zhou, Zhiqiang

doi:10.1016/j.measurement.2022.111712

Cited by 9 publications

(6 citation statements)

References 27 publications

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“…For the error modeling in Equations ( 31) and (32), the feedback correction for the navigation parameters is provided by Equation (33).…”

Section: Navigation Error State Model In the Inertial Framementioning

confidence: 99%

“…Subsequently, the observability of the system is analyzed based on the piecewise constant system (PWCS) observability method and singular value decomposition (SVD) observability analysis. Finally, the paper introduces backtracking navigation [ 31 , 32 ], enabling the sensor data to be reused to enhance the estimation accuracy within a short period.…”

Section: Introductionmentioning

confidence: 99%

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A Fast Self-Calibration Method for Dual-Axis Rotational Inertial Navigation Systems Based on Invariant Errors

Sun,

Lai,

Lyu

et al. 2024

Sensors

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In order to ensure that dual-axis rotational inertial navigation systems (RINSs) maintain a high level of accuracy over the long term, there is a demand for periodic calibration during their service life. Traditional calibration methods for inertial measurement units (IMUs) involve removing the IMU from the equipment, which is a laborious and time-consuming process. Reinstalling the IMU after calibration may introduce new installation errors. This paper focuses on dual-axis rotational inertial navigation systems and presents a system-level self-calibration method based on invariant errors, enabling high-precision automated calibration without the need for equipment disassembly. First, navigation parameter errors in the inertial frame are expressed as invariant errors. This allows the corresponding error models to estimate initial attitude even more rapidly and accurately in cases of extreme misalignment, eliminating the need for coarse alignment. Next, by utilizing the output of a gimbal mechanism, angular velocity constraint equations are established, and the backtracking navigation is introduced to reuse sensor data, thereby reducing the calibration time. Finally, a rotation scheme for the IMU is designed to ensure that all errors are observable. The observability of the system is analyzed based on a piecewise constant system method and singular value decomposition (SVD) observability analysis. The simulation and experimental results demonstrate that this method can effectively estimate IMU errors and installation errors related to the rotation axis within 12 min, and the estimated error is less than 4%. After using this method to compensate for the calibration error, the velocity and position accuracies of a RINS are significantly improved.

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“…For the error modeling in Equations ( 31) and (32), the feedback correction for the navigation parameters is provided by Equation (33).…”

Section: Navigation Error State Model In the Inertial Framementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Fast Self-Calibration Method for Dual-Axis Rotational Inertial Navigation Systems Based on Invariant Errors

Sun,

Lai,

Lyu

et al. 2024

Sensors

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show abstract

“…The optical axis center of the laser assembly is coincident with the optical axis center of the calibrator by adjusting the position of the calibrator on the front face of the calibrator. The image of the center of the cross cursor which is projected on the coordinate plate of the illuminometer probe by the laser module is collected through the camera module, and the image is uploaded to the computer control terminal [6][7][8][9] by the transmission system, the computer control terminal automatically identifies the coordinate value of the cross cursor center of the laser assembly on the image, and automatically controls the moving platform to drive the action of the calibrator, the center coordinates of the cross cursor projected by the laser assembly on the coordinate plate coincide with the center coordinates of the coordinate plate. The new method has the characteristics of high automatization, time saving and labor saving.…”

Section: Structural Design Of Alignment Devicementioning

confidence: 99%

Research on automatic identification and alignment device of the optical axis of calibrators for headlamp tester of motor vehicle

Dong-li

Wang

Dong

et al. 2023

Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023)

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The level and theodolite are used in the calibrator of the current automobile headlamp tester to align the optical axis center, this method needs many people to cooperate with the operation, the low degree of automation is insufficient. To solve the problem, this paper presents an automatic alignment device and method for calibrator optical axis of vehicle headlamp tester, introduces the structure, composition and principle of the alignment device and the specific implementation methods and steps. The comparison of experimental data shows that the alignment device has the advantages of high automation, simple operation and high accuracy. It can replace the existing level and theodolite to ensure the alignment of the luminous optical axis center of calibrators for headlamp tester of motor vehicle and the geometric center of the illuminometer probe.

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“…Initial alignment is one of the key technologies in inertial navigation [ 1 , 2 ], and the inertial navigation system (INS) needs to perform initial alignment before entering the navigation state during every startup. Due to the fact that inertial navigation calculation is an integral process, and initial alignment is actually a problem of determining the initial value of integration [ 3 ], the alignment result will directly affect the navigation accuracy of the system [ 4 ]. Therefore, INS requires accuracy for initial alignment.…”

Section: Introductionmentioning

confidence: 99%

Design of a Multi-Position Alignment Scheme

Guan,

Liu,

Wei

et al. 2024

Sensors

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The current new type of inertial navigation system, including rotating inertial navigation systems and three-autonomy inertial navigation systems, has been increasingly widely applied. Benefited by the rotating mechanisms of these inertial navigation systems, alignment accuracy can be significantly enhanced by implementing IMU (Inertial Measurement Unit) rotation during the alignment process. The principle of suppressing initial alignment errors using rotational modulation technology was investigated, and the impact of various component error terms on alignment accuracy of IMU during rotation was analyzed. A corresponding error suppression scheme was designed to overcome the shortcoming of the significant scale factor error of fiber optic gyroscopes, and the research content of this paper is validated through corresponding simulations and experiments. The results indicate that the designed alignment scheme can effectively suppress the gyro scale factor error introduced by angular motion and improve alignment accuracy.

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A high-accuracy initial alignment method based on backtracking process for strapdown inertial navigation system

Cited by 9 publications

References 27 publications

A Fast Self-Calibration Method for Dual-Axis Rotational Inertial Navigation Systems Based on Invariant Errors

A Fast Self-Calibration Method for Dual-Axis Rotational Inertial Navigation Systems Based on Invariant Errors

Research on automatic identification and alignment device of the optical axis of calibrators for headlamp tester of motor vehicle

Design of a Multi-Position Alignment Scheme

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