Transfer Alignment Configuration Based on Angular Velocity and Angular Velocity Integral Applied to Marine Vehicles

Document Type : Research Article

Authors

1 Faculty of Electrical and Computer Engineering, Malek-Ashtar University of technology, Tehran, Iran

2 Northern Reasearch Center for Science and Technology, Malek-Ashtar University of technology, Fereydunkenar, Mazandaran

Abstract

Transfer alignment of master and slave systems plays a key role in the inertial navigation accuracy of the marine cooperative vehicles. Accuracy enhancement of misalignment angle and orientation estimation is the main purpose of the transfer alignment. Velocity and orientation matching is a well-known method for transfer alignment. However, in many applications, there are no velocity measurements of both the master and slave systems due to weight, dimensional and technological limitations of accurate speed sensors, such as Doppler Velocity Loggers (DVL). Angular velocity configuration is a suitable solution for transfer alignment in this situation. However, the orientation error cannot be estimated in this configuration. Taking this drawback into account, a new configuration based on using the integral of angular velocity in addition to angular velocity measurement is presented for transfer alignment in the current research. Furthermore, appropriate abilities are considered to estimate the dynamic misalignment angle, orientation error and also measurement errors of the slave gyroscope. Two linear and non-linear observation models are developed for the transfer alignment configuration. The simulation results reveal the appropriate performance of the proposed configuration for marine application, especially when there are no accurate velocity measurements. Based on the simulation results, the performance of the non-linear observation model is better than linear ones in dynamic misalignment angle estimation. Moreover, it can be inferred from the orientation error estimation that rich data in high-maneuvered motion is necessary for required estimation accuracy. Additionally, 200 runs of Monte-Carlo simulation are developed and the estimation RMSE are presented.

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References

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AUT Journal of Modeling and Simulation
Volume 54, Issue 1
June 2022
Pages 31-44

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