Adaptive filtering design for in-motion alignment of INS

Author

Tong Liu ; Qian Xu ; Yuejun Li

Author_Institution

Sch. of Autom., Beijing Inst. of Technol., Beijing, China

fYear

2014

fDate

May 31 2014-June 2 2014

Firstpage

2669

Lastpage

2674

Abstract

Misalignment angles estimation of strapdown inertial navigation system (INS) using global positioning system (GPS) data is highly affected by measurement noises, especially with noises displaying time varying statistical properties. Hence, adaptive filtering approach is recommended for the purpose of improving the accuracy of in-motion alignment. In this paper, a simplified form of Celso´s adaptive stochastic filtering is derived and applied to estimate both the INS error states and measurement noise statistics. To detect and bound the influence of outliers in INS/GPS integration, outlier detection based on jerk tracking model is also proposed. The accuracy and validity of the proposed algorithm is tested through ground based navigation experiments.

Keywords

Global Positioning System; adaptive filters; filtering theory; inertial navigation; statistical analysis; stochastic processes; Celso adaptive stochastic filtering; GPS data; INS; INS-GPS integration; adaptive filtering approach; global positioning system; in-motion alignment; jerk tracking model; misalignment angle estimation; outlier detection; strapdown inertial navigation system; time varying statistical properties; Global Positioning System; Kalman filters; Mathematical model; Noise; Noise measurement; Vehicles; INS/GPS integration; adaptive filtering; in-motion alignment; outlier detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (2014 CCDC), The 26th Chinese

Conference_Location

Changsha

Print_ISBN

978-1-4799-3707-3

Type

conf

DOI

10.1109/CCDC.2014.6852624

Filename

6852624