Multisensor Data Fusion in Adaptive Astro-Satellite-Inertial Navigation System

Author

Fokin, Leonid A.

Author_Institution

South Ural State Univ., Chelyabinsk

fYear

2007

fDate

20-21 April 2007

Firstpage

22

Lastpage

28

Abstract

This paper presents the fusion algorithm for navigation information from three distinct sources: strapdown inertial navigation system (SINS), GPS receiver and astronavigation system (ANS) i.e. for SINS/ANS/GPS integrated navigation system in the presence of non- stationary Gaussian noise. Adaptive innovation-based (maximum-likelihood covariance) Kalman filter is used to estimate errors of SINS position, velocity, attitude, accelerometers, gyroscopes and gravitation acceleration to yield improved integrated navigation solution. First order Gauss-Markov processes are used to simulate time-correlation of SINS and GPS errors. Lagrange polynomials are used to interpolate data from each source of navigation information with different output rates.

Keywords

Gaussian noise; Global Positioning System; Kalman filters; Markov processes; inertial navigation; maximum likelihood estimation; sensor fusion; GPS receiver; Gauss-Markov processes; adaptive astro-satellite-inertial navigation system; maximum-likelihood covariance Kalman filter; multisensor data fusion; navigation information; nonstationary Gaussian noise; Acceleration; Accelerometers; Adaptive systems; Gaussian noise; Global Positioning System; Gyroscopes; Inertial navigation; Maximum likelihood estimation; Silicon compounds; Yield estimation; Integrated navigation system; SINS/ANS/GPS; aided SINS; astro-satellite-inertial navigation; stellar-inertial navigation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Communications, 2007. SIBCON '07. Siberian Conference on

Conference_Location

Tomsk

Print_ISBN

1-4244-0346-4

Type

conf

DOI

10.1109/SIBCON.2007.371294

Filename

4233273