DocumentCode :
231454
Title :
Research on the algorithm of gravity aided Inertial Navigation based on CKF
Author :
Hao Xiong ; Xingshu Wang ; Jing Zhu ; Dongkai Dai
Author_Institution :
Coll. of Opto-Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2014
fDate :
19-23 Oct. 2014
Firstpage :
252
Lastpage :
257
Abstract :
Using the information of gravity filed for aided inertial navigation can ensure the system´s passive resistance and anti-jamming, and has become the hot topic of integrated navigation field. In this paper, we establish state-space model derived from the error equation of Inertial Navigation System (INS), and set the difference between indicated gravity anomaly and measured gravity anomaly which contains the information of position error as the measurement. After that, Cubature Kalman Filter (CKF) is introduced for estimation of navigation error online, which avoids the linearization of measurement. At last, the simulation system is realized based on the DNSC08 gravity model to inspect and verify the algorithm. The simulation results show that, the algorithm based on CKF for gravity aided navigation can strength the system´s performance effectively.
Keywords :
Kalman filters; gravity; inertial navigation; CKF; DNSC08 gravity model; INS; cubature Kalman filter; gravity aided inertial navigation system; gravity anomaly; state-space model; Gravity; Gravity measurement; Inertial navigation; Mathematical model; Measurement uncertainty; Position measurement; CKF; Gravity aided navigation; INS; gravity anomaly;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing (ICSP), 2014 12th International Conference on
Conference_Location :
Hangzhou
ISSN :
2164-5221
Print_ISBN :
978-1-4799-2188-1
Type :
conf
DOI :
10.1109/ICOSP.2014.7015007
Filename :
7015007
Link To Document :
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