Application of Kalman Filter algorithm in gravity-aided navigation system

Author

Liu, Fanming ; Li, Yan ; Zhang, Yingfa ; Hou, Huijuan

Author_Institution

Coll. of Autom., Harbin Eng. Univ., Harbin, China

fYear

2011

fDate

7-10 Aug. 2011

Firstpage

2322

Lastpage

2326

Abstract

To restrain the error of inertial navigation system (INS), gravity-aided navigation system is introduced. The principle of gravity-aided navigation system is expatiated. By using Kalman Filter, error correcting of inertial navigation system comes true. Extended Kalman Filter (EKF) model is derived, and a method of gravity filed linearization is given. Based on the analysis of the shortage of EKF, Unscented Kalman Filter (UKF) algorithm is established. UKF is a nonlinear filter algorithm. Simulation results proved that the methods of EKF and UKF can effectively depress the error of INS.

Keywords

Kalman filters; error correction; inertial navigation; linearisation techniques; nonlinear filters; error correction; extended Kalman filter algorithm; gravity field linearization; gravity-aided navigation system; inertial navigation system; nonlinear filter algorithm; underwater navigation; unscented Kalman filter algorithm; Equations; Filtering algorithms; Gravity; Kalman filters; Mathematical model; Navigation; Noise; EKF; Gravity-aided Navigation; INS; UKF;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics and Automation (ICMA), 2011 International Conference on

Conference_Location

Beijing

ISSN

2152-7431

Print_ISBN

978-1-4244-8113-2

Type

conf

DOI

10.1109/ICMA.2011.5986348

Filename

5986348