【正文】 exhibit noiselike behavior with deviations in the order of tens of meters due to the ‘‘clockjump’’ elimination procedure mentioned previously. Therefore, the parably large process noise has been chosen to pensate for these deviations. The ambiguities of the carrier phase measurements are assumed to be constant parameters and therefore no process noise is introduced. Upon filter initialization, the initial covariance matrix is set up as a diagonal matrix with the square of the initial standard deviation on the main diagonal. Table 1 provides an overview of the filter settings. In the next step, the filter state is propagated towards the first epoch where measurements are available. During preprocessing in the following step, the ground station clock jumps are eliminated from the data as previously explained. Additionally, the observables are screened for missing data and satellites, which have dropped below an elevation cutoff angle of 10. The core part of the data screening is an integrity monitoring which is performed on the pseudo range and the carrier phase measurements in order to detect and remove outliers. During this monitoring,the orbits and clocks of the predicted IGU product are used together with the known station position to pute the residuals of the ionospherefree observations for each satellite. Since the position is known, only the station clock offset, which is mon for all measurements, must be puted and removed from the residuals. If the RMS of the pseudo ranges exceeds a predefined threshold, the residuals are recursively reputed with a single satellite excluded at a time. The bination, which yields the lowest residual, identifies the satellite with the outlier in the pseudo range measurement. This satellite is excluded from the filter at this epoch. If the residualthreshold is still exceeded, the procedure of recursively excluding satellite is repeated until the threshold is met or the number of valid satellites drops to two. In the latter case, all remaining satellites are rejected as well, since the monitoring procedure cannot further be performed. A similar approach has been chosen for the monitoring and screening of the carrier phase measurements, but instead time differences of the carrier phases between the current and the previous epoch are used, in order to avoid the plication of estimating ambiguities at this step. With this monitoring procedure,measurement outliers and cycle slips can be detected and the associated satellites are excluded from the measurement update. Afterwards, the ambiguities in the state vector are examined. If satellites have dropped below the elevation limit of the filter or are no longer tracked, their ambiguities are deleted and the space in the filter state is freed. If satellites are newly acquired, their ambiguities are initialized using codecarrier differences to provide their initial values. In addition, ambiguities of satellites, which have been rejected during the data screening, are removed from the filter and initialized again as soon as valid measurements for the satellite are available. Prior to the measurement update the filter applies a clock constraint, since the mean of all GPS satellite clocks is unobservable in the system. The clock constraint is applied as a ‘‘pseudo’’measurement update, which treats the mean of all clock offsets in the IGU clock product as observation of the mean clock offset in the filter , the filter clock estimates are tied to the predicted mean IGU clock, which is serves as a virtual referenceclock. Special care has been taken in modeling the pseudo range and carrier phase observations in the measurement update. Table 2 summarizes the used models and the measurement update of the filter, the state vector and the associated covariance matrix are stored for potential usage in the smoother. The procedure is iterated until all epochs have been processed. If smoothing of the results is not desired, they are stored in an SP3file, which consists of the ultrarapid orbit interpolated to 30 s original clock parameters from the ultrarapid file are replaced by the filter results.If the smoother shall be used, the filter is again initialized to process the plete data arc backwards in time starting at the end. The processing scheme is identical to the forward filter. After the backward run is finished, the smoother putes the mean of the forward and backward results of the filter state weighted according to theircovariance. The filter requires some time after initialization during which the filter state converges and the puted covariance decreases. Consequently, at the beginning of the data interval, the bad estimates of the forward filte