DocumentCode :
2815271
Title :
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
Link To Document :
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