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Sensors 2017, 17(12), 2709; https://doi.org/10.3390/s17122709

A Polar Initial Alignment Algorithm for Unmanned Underwater Vehicles

College of Automation, Harbin Engineering University, Harbin 150001, China
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Received: 10 October 2017 / Revised: 20 November 2017 / Accepted: 20 November 2017 / Published: 23 November 2017
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Abstract

Due to its highly autonomy, the strapdown inertial navigation system (SINS) is widely used in unmanned underwater vehicles (UUV) navigation. Initial alignment is crucial because the initial alignment results will be used as the initial SINS value, which might affect the subsequent SINS results. Due to the rapid convergence of Earth meridians, there is a calculation overflow in conventional initial alignment algorithms, making conventional initial algorithms are invalid for polar UUV navigation. To overcome these problems, a polar initial alignment algorithm for UUV is proposed in this paper, which consists of coarse and fine alignment algorithms. Based on the principle of the conical slow drift of gravity, the coarse alignment algorithm is derived under the grid frame. By choosing the velocity and attitude as the measurement, the fine alignment with the Kalman filter (KF) is derived under the grid frame. Simulation and experiment are realized among polar, conventional and transversal initial alignment algorithms for polar UUV navigation. Results demonstrate that the proposed polar initial alignment algorithm can complete the initial alignment of UUV in the polar region rapidly and accurately. View Full-Text
Keywords: unmanned underwater vehicle; initial alignment; grid frame; polar region unmanned underwater vehicle; initial alignment; grid frame; polar region
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Yan, Z.; Wang, L.; Wang, T.; Zhang, H.; Zhang, X.; Liu, X. A Polar Initial Alignment Algorithm for Unmanned Underwater Vehicles. Sensors 2017, 17, 2709.

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