Central difference Gaussian Particle filter for initial alignment of strapdown inertial navigation system

Shoucai Sun*, Chunlei Song, Junhou Wang, Xingtai Yao, Ling Xie

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The error model of the initial alignment of the marine strapdown inertial navigation system is nonlinear, while the azimuth angle error is large on the swaying base. For this nonlinear model, a new nonlinear filter called as the central difference Gaussian Particle filter is proposed, which is based on the central difference Kalman filter and the Gaussian Particle filter. The central difference Kalman filter is used to calculate the estimate value and the covariance matrix in the observation update for the distribution function, which is sampled as the importance density function for the Gaussian Particle filter. The simulation results demonstrate the novel filter has better estimation performance than the unscented Kalman filter and the Gaussian Particle filter for the initial alignment.

Original languageEnglish
Title of host publicationProceedings of 2010 International Conference on Intelligent Control and Information Processing, ICICIP 2010
Pages97-101
Number of pages5
EditionPART 2
DOIs
Publication statusPublished - 2010
Event2010 International Conference on Intelligent Control and Information Processing, ICICIP 2010 - Dalian, China
Duration: 13 Aug 201015 Aug 2010

Publication series

NameProceedings of 2010 International Conference on Intelligent Control and Information Processing, ICICIP 2010
NumberPART 2

Conference

Conference2010 International Conference on Intelligent Control and Information Processing, ICICIP 2010
Country/TerritoryChina
CityDalian
Period13/08/1015/08/10

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