Next Article in Journal
Smartphone Applications with Sensors Used in a Tertiary Hospital—Current Status and Future Challenges
Next Article in Special Issue
A Novel Artificial Fish Swarm Algorithm for Recalibration of Fiber Optic Gyroscope Error Parameters
Previous Article in Journal
A PDMS-Based 2-Axis Waterproof Scanner for Photoacoustic Microscopy
Previous Article in Special Issue
Integration of GPS Precise Point Positioning and MEMS-Based INS Using Unscented Particle Filter
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(5), 9827-9853; doi:10.3390/s150509827

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)

Abstract

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
Figures

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).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

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.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top