A Robust Positioning Technique in DR/GPS using the Receding Horizon Sigma Point Kalman FIR Filter

Abstract

This paper describes the receding horizon sigma point Kalman FIR filter for tightly coupled DR/GPS hybrid navigation system. In order to overcome the flaws of the EKF, the SPKF is merged with the receding horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, and etc. The computational burden is reduced. Especially, the RHSPKF filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can be occurred in the MEMS inertial sensors by temperature variation. Therefore, the RHSPKF filter can provide the navigation information with good quality in the DR/GPS hybrid navigation system seamlessly