Robust Positioning Technique in Low-Cost DR/GPS for Land Navigation

Abstract

This paper describes a dead-reckoning (DR) construction for land navigation and sigma-point-based receding-horizon Kalman finite-impulse response (SPRHKF) filter for DR/GPS integration system. A simple DR construction is adopted to improve the performance of both pure land DR navigation and DR/GPS integration system. In order to overcome the flaws of the extended Kalman filter (EKF), the sigma-point KF (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, etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can occur in the microelectromechanical systems' inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS integration system for land navigation seamlessly