A new method to abstract the noise model in INS/GNS integrated navigation system

Author

Zhangjingwei ; Songming ; Rensicong

Author_Institution

Northwestern Polytech. Univ., Xi´´an, China

fYear

2001

fDate

2001

Firstpage

1169

Lastpage

1172

Abstract

In this paper, we provide a new practical method of abstracting the noise model of an INS/GNSS integrated navigation system from measuring data. After deductively designing the experiment, we carried out tests of the stationary stochastic process on logged GNSS data. The noise model was then fitted to the data and the parameters estimated. The design uses a classical cascaded Kalman filter based on position and velocity integration and applies the theory of stochastic processes, probability statistics, time series analysis and system identification. This method, we think, can be used practically in other integrated navigation systems

Keywords

Kalman filters; inertial navigation; noise; parameter estimation; position measurement; probability; satellite navigation; stochastic processes; time series; GNSS logged data; INS; cascaded Kalman filter; global navigation satellite system; inertial navigation system; integrated navigation system; measured data analysis; noise model extraction; noise model fitting; noise model parameters; position integration; probability statistics; stationary stochastic process tests; stochastic processes; time series analysis; velocity integration; Colored noise; Equations; Gaussian noise; Noise measurement; Position measurement; Satellite navigation systems; State estimation; Stochastic processes; Velocity measurement; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 2001 CIE International Conference on, Proceedings

Conference_Location

Beijing

Print_ISBN

0-7803-7000-7

Type

conf

DOI

10.1109/ICR.2001.984918

Filename

984918