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Sensors 2015, 15(5), 9827-9853;

A Self-Alignment Algorithm for SINS Based on Gravitational Apparent Motion and Sensor Data Denoising

Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China,
Author to whom correspondence should be addressed.
Academic Editor: Gert F. Trommer
Received: 22 November 2014 / Revised: 12 March 2015 / Accepted: 21 April 2015 / Published: 27 April 2015
(This article belongs to the Special Issue Inertial Sensors and Systems)
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Initial alignment is always a key topic and difficult to achieve in an inertial navigation system (INS). In this paper a novel self-initial alignment algorithm is proposed using gravitational apparent motion vectors at three different moments and vector-operation. Simulation and analysis showed that this method easily suffers from the random noise contained in accelerometer measurements which are used to construct apparent motion directly. Aiming to resolve this problem, an online sensor data denoising method based on a Kalman filter is proposed and a novel reconstruction method for apparent motion is designed to avoid the collinearity among vectors participating in the alignment solution. Simulation, turntable tests and vehicle tests indicate that the proposed alignment algorithm can fulfill initial alignment of strapdown INS (SINS) under both static and swinging conditions. The accuracy can either reach or approach the theoretical values determined by sensor precision under static or swinging conditions. View Full-Text
Keywords: strapdown inertial navigation (SINS); self-alignment; gravitational apparent motion; denoising strapdown inertial navigation (SINS); self-alignment; gravitational apparent motion; denoising

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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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Liu, Y.; Xu, X.; Liu, X.; Yao, Y.; Wu, L.; Sun, J. A Self-Alignment Algorithm for SINS Based on Gravitational Apparent Motion and Sensor Data Denoising. Sensors 2015, 15, 9827-9853.

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