GPS based land vehicle positioning using Gaussian sum filters

In this paper, we consider land vehicle positioning in an urban environment. A nonlinear and non-Gaussian model is derived as the process model whereas GPS pseudo-range and odometer measurements are used as observations. A parametric model is proposed for representing the variations of the observation noise covariance matrix. The performances of the derived Gaussian sum filter are evaluated by using experimental data.