Cubature + Extended Hybrid Kalman Filtering Method and Its Application in PPP/IMU Tightly Coupled Navigation Systems

Abstract

Implementing the GPS (Global Positioning System) total carrier phase observations based on the PPP (Precise Point Positioning) technique in a navigation Kalman filter can improve the position accuracy of a GPS/IMU (Inertial Measurement Unit) tightly-coupled navigation system to the sub-meter level. However, the carrier phase implementation introduces extra states like ambiguities, to the Kalman filter state vector, which increases the computational burden especially when nonlinear filtering methods are applied. In this paper, in order to reduce the computational burden of the PPP/IMU tightly-coupled navigation system, a CKF (Cubature Kalman Filter)+EKF (Extended Kalman Filter) hybrid filtering method by applying a linear filtering method to estimate the linear states mainly GPS related states, while a nonlinear filtering method to estimate the nonlinear states like IMU related states, is proposed. The hybrid filtering method can make a balance between keeping the CKF benefits in dealing with nonlinear problems and reducing the computational time. The simulation and experiment results show the effectiveness of the method.Index Terms-Cubature Kalman filter, Extended Kalman filter, PPP, IMU, Hybrid filtering method 1530-437X (c)

Robust measure of non‐linearity‐based cubature Kalman filter

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Online cubature Kalman filter Rauch–Tung–Striebel smoothing for indoor inertial navigation system/ultrawideband integrated pedestrian navigation

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