Kalman filter based on error state variables in SINS + GPS navigation application

Kalman filter (KF) is widely used in SINS + GPS-guided combination method, but the sensor's mathematical model of the transporter is generally nonlinear, so the complexity and computation of the model are large. In this paper, we present an Kalman filter algorithm based on error state variables...

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Bibliographic Details
Main Authors: Xiaolin Hou, Yan Yang, Fengying Li, Zhanrong Jing
Format: Conference Proceeding
Language:English
Subjects:
Equations
Global Positioning System
Markov processes
Mathematical model
Silicon compounds
White noise
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Summary:Kalman filter (KF) is widely used in SINS + GPS-guided combination method, but the sensor's mathematical model of the transporter is generally nonlinear, so the complexity and computation of the model are large. In this paper, we present an Kalman filter algorithm based on error state variables in SINS + GPS navigation application. The mathematical model of the errors of GPS data and inertial navigation data is linear, so the errors are taken as the states, which avoids the complexity caused by nonlinear and makes the design difficulty reduced significantly. This paper also gives the design process and the mathematical model of navigation system, and sets the state parameters of the model. Finally, simulation results show the effectiveness of the algorithm.
ISSN:2164-4357
DOI:10.1109/ICIST.2011.5765358