Noise Characteristics in High Precision GPS Positioning

In this contribution we present the results of three different studies in which the method of least-squares variance component estimation (LS-VCE) was used to infer the stochastic properties of GPS data. The three studies cover the GPS geometry-free model, the GPS coordinate time series model, and the GPS zero-baseline model. In the GPS geometry-free model, LS-VCE is applied to assess the precision of different observation types, correlation between observation types on L1 and L2, and satellite elevation dependence of the GPS observables precision. We show, for example, that the precision of code observations (for zero baseline) ranges from 10 to 15 cm depending on the satellite elevation and the type of the receiver used. The LSVCE time series analysis pertains to data of various permanent GPS tracking stations. It reveals that the noise can be divided into two components, namely white noise and flicker noise. We show that both noise components are spatially correlated (e.g. a correlation coefficient of about 0.8 over short distances between permanent stations). Finally, in the (classical) zero-baseline model, nonlinear LS-VCE is applied to assess the noise characteristics of GPS receivers based on covariance functions.