DocumentCode :
691253
Title :
SINS/SRCNS Integrated Navigation Method Based on MME/KF Algorithm
Author :
Qian Hua-ming ; Sun Long
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
fYear :
2013
fDate :
21-23 Sept. 2013
Firstpage :
1624
Lastpage :
1629
Abstract :
The positioning accuracy of traditional SINS/CNS integrated navigation system is low, because of the limitation of level benchmark. So strap-down inertial navigation system/stellar refraction celestial navigation system integrated navigation method (SINS/SRCNS) based on starlight refraction method is proposed. The model errors which are uncertain exist in measurement equation are estimated by Minimum Mode error Estimation (MME) and backward inference algorithm. Then the Kalman Filter is used to estimate system´s states, this entire process formed the MME/KF algorithm. The simulation results indicated that, the proposed method is not only able to estimate the gyro drift exactly, but also to correct the navigation error caused by the accelerometer bias, and bate the divergence of speed and position error ulteriorly, therefore it is a practical method to improve the positioning accuracy.
Keywords :
Kalman filters; accelerometers; gyroscopes; inertial navigation; Kalman filters; MME/KF algorithm; SINS-SRCNS integrated navigation method; accelerometer bias; backward inference algorithm; gyro drift; minimum mode error estimation; positioning accuracy; starlight refraction method; stellar refraction celestial navigation system; strap-down inertial navigation; Atmospheric modeling; Equations; Mathematical model; Measurement uncertainty; Navigation; Silicon compounds; Vectors; MME; atmospheric refraction model; integrated navigation; starlight refraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2013 Third International Conference on
Conference_Location :
Shenyang
Type :
conf
DOI :
10.1109/IMCCC.2013.360
Filename :
6840750
Link To Document :
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