The performance comparison and analysis of extended Kalman filters for GPS/DR navigation

Abstract This paper proposes several nonlinear filtering algorithms based on the global positioning system (GPS) and the dead reckoning (DR). To achieve high location and velocity accuracy, the first-order extended Kalman filter (FEKF), the second EKF (SEKF) and EKF-Rauch-Tung-Striebel (EKF-RTS) smoother are introduced for GPS/DR integrated navigation system. And the algorithms of the FEKF, SEKF and EKF-RTS are given. Furthermore, the state models and measurement models of GPS/DR are set up. For comparison purpose, the GPS/DR integrated navigation system based on the three algorithms is simulated, and the algorithm performance is analyzed and compared by the simulation results of FEKF, SEKF, FEKF-RTS and SEKF-RTS. Numerical results demonstrate that the EKF-RTS gives clearly better estimates than the FEKF and SEKF.

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