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Sensors 2016, 16(5), 621; doi:10.3390/s16050621

An Improved Alignment Method for the Strapdown Inertial Navigation System (SINS)

College of Automation, Harbin Engineering University, Harbin 150001, China
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Author to whom correspondence should be addressed.
Academic Editor: Jörg F. Wagner
Received: 8 March 2016 / Revised: 21 April 2016 / Accepted: 23 April 2016 / Published: 29 April 2016
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)
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Abstract

In this paper, an innovative inertial navigation system (INS) mechanization and the associated Kalman filter (KF) are developed to implement a fine alignment for the strapdown INS (SINS) on stationary base. The improved mechanization is established in the pseudo-geographic frame, which is rebuilt based on the initial position. The new mechanization eliminates the effects of linear movement errors on the heading by decoupling. Compared with the traditional local-level mechanization, it has more advantages. The proposed algorithm requires lower coarse alignment accuracy in both the open-loop and closed-loop KFs and hence can improve the system reliability and decrease the total alignment time. Moreover, for the closed-loop KF, it can decrease oscillation caused by the system errors and improve the closed-loop system stability. In addition, the proposed algorithm can also be applied to polar alignment. The performance of the proposed algorithm is verified by both simulations and experiments and the results exhibit the superior performance of the proposed approach. View Full-Text
Keywords: polar alignment; pseudo-frame; decoupling; Kalman filter polar alignment; pseudo-frame; decoupling; Kalman filter
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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Liu, M.; Gao, Y.; Li, G.; Guang, X.; Li, S. An Improved Alignment Method for the Strapdown Inertial Navigation System (SINS). Sensors 2016, 16, 621.

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