Information-reusing alignment technology for rotating inertial navigation system

Fu, Qing; Li, Sihai; Liu, Yang; Wu, Feng

doi:10.1016/j.ast.2020.105747

Cited by 33 publications

(11 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The idea of MIMU data generation is to superimpose errors on the original gyroscope and accelerometer data corresponding to Figure 6 to simulate lower-precision MEMS inertial sensor data. The error components of the gyroscope and accelerometer include repeatability biases, slow-varying drifts, and fast-varying drifts [4,5]. The repeatability biases can be regarded as a random constant.…”

Section: Methodsmentioning

confidence: 99%

“…The micro-electromechanical inertial measurement unit (MIMU) is especially favored by the mine engineers with the advantages of low cost and small size. However, the free inertial position error can grow quickly over time due to the drifting of the inertial devices [1], which includes repeatability biases, the slow-varying drifts, and the fast-varying drifts [4,5], and thus the integrated navigation mode with MIMU as the core component becomes a better choice. The MIMU/Global Positioning System (GPS) integrated navigation system is widely used as a conventional and low-cost positioning method.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on the Shearer Positioning Method Based on the MEMS Inertial Sensors/Odometer Integrated Navigation System and RTS Smoother

Zheng

Liu

et al. 2021

Micromachines

Self Cite

View full text Add to dashboard Cite

The shearer positioning method with an inertial measurement unit and the odometer is feasible in the longwall coal-mining process. However, the positioning accuracy will continue to decrease, especially for the micro-electromechanical inertial measurement unit (MIMU). In order to further improve the positioning accuracy of the shearer without adding other external sensors, the positioning method of the Rauch-Tung-Striebel (RTS) smoother-aided MIMU and odometer is proposed. A Kalman filter (KF) with the velocity and position measurements, which are provided by the odometer and closing path optimal estimation model (CPOEM), respectively, is established. The observability analysis is discussed to study the possible conditions under which the error states of KF can be estimated. A RTS smoother with the above-mentioned KF as the forward filter is built. Finally, the experiments of simulating the movement of the shearer through a mobile carrier were carried out, with a longitudinal movement distance of 44.6 m and a lateral advance distance of 1.2 m. The results show that the proposed method can effectively improve the positioning accuracy. In addition, the odometer scale factor and mounting angles can be estimated in real time.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on the Shearer Positioning Method Based on the MEMS Inertial Sensors/Odometer Integrated Navigation System and RTS Smoother

Zheng

Liu

et al. 2021

Micromachines

Self Cite

View full text Add to dashboard Cite

show abstract

“…These algorithms are used to calculate a coarse attitude, and the fine initial attitude will be estimated after modeling the error model of SINS, estimating attitude errors of coarse aligning result, and analysing the state observablity degree. The error model is mainly divided into little-misalignment inertial model [5] and large-misalignment nonlinear model [6], [7], [8]. UKF (Unsented Kalman Filter) is usually used to estimate attitude error of nonlinear model, because large-misalignment error model of SINS is strong-nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

A GNSS Aided Initial Alignment Method for MEMS-IMU Based on Backtracking Algorithm and Backward Filtering

Yang¹,

Yan²,

Hao³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

To obtain a high-accuracy position with SINS(Strapdown Inertial Navigation System), initial alignment needs to determine initial attitude rapidly and accurately. Highaccuracy grade IMU(Inertial Measurement Uint) can obtain the initial attitude indenpendently, however, the low-accuracy grade gyroscope doesn't adapt to determine the heading angle, hence the initial attitude matrix will not be obtained. If using large misalignment angle model to estiamting heading angle, the convergence time will become much longer. For solving these two problems, a novel alignment algorithm combined backtracking algorithm and reverse navigation updating method with GNSS(Global Navigation Satellite System) aiding is proposed herein. The simulation and land vehicle test were finished to evaluate the alignment accuracy of the proposed algorithm. The horizontal misalignment is less than 2.3 arcmin and the heading misalignment is less than 10.1 arcmin in test. The proposed algorithm is a feasible and practical alignment method for low-cost IMU to obtain initial attitude in short term and large misalignment condition aided by GNSS.

show abstract

“…At the same time, the attitude quaternion and velocity increment are recorded at a lower frequency. In the subsequent fine alignment stage, the stored data is used to complete the backtracking navigation and Kalman filter calculation in the local geographic coordinate system [17].…”

Section: Introductionmentioning

confidence: 99%

Research on Fast Self-alignment Method of SINS under Vehicle Jitter and Leveling Disturbance

Yang

et al. 2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Using the combination of simulation and actual measurement, analyze the impact of disturbances such as the jitter of the launch vehicle drive motor and the leveling motion of the launch vehicle on the output signals of the gyroscope and accelerometer, clarify the alignment error source of the SINS, and combine the error model to design based on the Kalman classical filter. For the algorithm’s variable mode filtering scheme, a variable mode filtering alignment method using the output pulse threshold of the horizontal gyro is proposed, and the filtering method in the fine alignment stage is improved. Vehicle experiments show that the proposed variable mode filtering method has a simple algorithm and a small amount of calculation, and can effectively suppress dynamic disturbances such as engine jitter and vehicle leveling motion, improve the convergence speed of the azimuth error of the strapdown inertial navigation system, and reduce the azimuth misalignment angle estimate bias.

show abstract

Information-reusing alignment technology for rotating inertial navigation system

Cited by 33 publications

References 19 publications

Research on the Shearer Positioning Method Based on the MEMS Inertial Sensors/Odometer Integrated Navigation System and RTS Smoother

Research on the Shearer Positioning Method Based on the MEMS Inertial Sensors/Odometer Integrated Navigation System and RTS Smoother

A GNSS Aided Initial Alignment Method for MEMS-IMU Based on Backtracking Algorithm and Backward Filtering

Research on Fast Self-alignment Method of SINS under Vehicle Jitter and Leveling Disturbance

Contact Info

Product

Resources

About