Sigma-Point Kalman Filters for GPS Based Position Estimation

Stand-alone GPS based position estimation problem using GPS raw data, pseudo-range and Doppler shifts measurements are the concept of fusing noisy observations. A family of improved derivative nonlinear Kalman filters called sigma point Kalman filter (SPKF) are applied to a nonlinear model of GPS based position estimation in this paper. Simulations are made to compare the filter with the traditional iterative least square (ILS) method and extended Kalman filter (EKF) method, results indicate that under same conditions, SPKF has higher filtering accuracy and more stable estimation performance

[1]  Rudolph van der Merwe,et al.  The square-root unscented Kalman filter for state and parameter-estimation , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[2]  Rudolph van der Merwe,et al.  Efficient derivative-free Kalman filters for online learning , 2001, ESANN.

[3]  Alice M. Agogino,et al.  Intelligent Sensor Validation And Sensor Fusion For Reliability And Safety Enhancement In Vehicle Control , 1995 .

[4]  Hugh F. Durrant-Whyte,et al.  A Kalman filter model for GPS navigation of land vehicles , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[5]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[6]  Rudolph van der Merwe,et al.  Sigma-point kalman filters for probabilistic inference in dynamic state-space models , 2004 .

[7]  Niels Kjølstad Poulsen,et al.  New developments in state estimation for nonlinear systems , 2000, Autom..

[8]  H.F. Durrant-Whyte,et al.  A new approach for filtering nonlinear systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[9]  M. Pachter,et al.  GPS estimation algorithm using stochastic modeling , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[10]  Yongsheng Wang,et al.  Unmanned space vehicle navigation by GPS , 1996 .

[11]  Hideki Hashimoto,et al.  Investigation on nonlinear filtering algorithms for GPS , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[12]  S. Haykin.  Kalman Filtering and Neural Networks , 2001 .