Optimal tracking filter considering both correlated/white measurement noise

In this paper, a dynamic modeling method for the velocity and position information of a single frequency stand-alone GPS (Global Positioning System) receiver is described. In static condition, the position error dynamic model is identified as a first/second order transfer function, and the velocity error model is identified as a band-limited Gaussian white noise via non-parametric method of a PSD (Power Spectrum Density) estimation in continuous time domain. A Kalman filtering method is proposed that consider both correlated/white measurements noise based on identified GPS error model. The performance of the proposed Kalman filtering method is verified via numerical simulation.