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

Abstract

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.