Application of Optimization Technique for GPS Navigation Kalman Filter Adaptation

Authors:
Dah-Jing Jwo;Shun-Chieh Chang
Affiliations:
Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung, Taiwan 20224;Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung, Taiwan 20224
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Year:
2008

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Abstract

The position-velocity (PV) process model can be applied to the GPS Kalman filter adequately when navigating a vehicle with constant speed. However, when an abrupt acceleration motion occurs, the filtering solution becomes very poor or even diverges. To avoid the limitation of the Kalman filter, the particle swarm optimization can be incorporated into the filtering mechanism as dynamic model corrector. The PSO can be utilized as the noise-adaptive mechanism to tune the covariance matrix of process noise and overcome the deficiency of Kalman filter. In this paper, PSO-aided Kalman filter approach is employed for tuning the covariance of the GPS Kalman filter so as to reduce the estimation error during substantial maneuvering. Performance evaluation for the PSO-aided Kalman filter as compared to the conventional Kalman filter is provided.