GPS receivers can provide sufficient accuracy in many environments. However, the GPS signals are very weak at the surface of the earth and they can easily be jammed. The GPS signal experiences reflection, scattering and attenuation in urban environments, and these effects may cause large position errors. Thus, the position accuracy and availability is often insufficient in urban environments, especially considering indoor operations. The main goal of this work was to determine whether the position solution as delivered by a GPS receiver is reliable enough. That is, for each point in time we wish to decide whether the position error in the GPS solution is acceptable or not, based on information that is available in a standard hand-held GPS receiver. Whether a position solution is useful or not depends on the application at hand. The intention with this work is that it should be possible to determine both 1) whether a GPS position is reliable enough as a stand-alone navigation solution or not and 2) whether the GPS receiver should be used in a multisensor navigation solution or be left out. Field trials were performed to collect data to 1) determine which metrics that could be used to estimate the position error and determine the position reliability, and 2) use for training and evaluation of estimation and classification performance. The standard deviation of latitude and longitude delivered by the NMEA GST message can be used as an estimate of the position error for any GPS receiver that supports the standard GST message. The position error is estimated quite well, using the NMEA GST standard deviations, in good and poor conditions (such as indoors). However, in areas with heavily varying channel conditions and multipath propagation, such as in urban areas, the estimation becomes more difficult. We have also shown that there is a strong correlation between the position error and numerous other metrics, and that these metrics also can be used to estimate the position error. However, we have not been able to exploit these other measures to make a significant improvement in terms of the estimation and classification performance, as compared to using the NMEA GST standard deviations only. The main difficulty in exploiting other metrics for estimation and classification was due to an unknown delay from the point in time when the parameter changes until the position error starts drifting away, and from when the metrics recover until the position accuracy is regained. The delay is caused by internal filtering of the position solution in the GPS receiver. This delay depends heavily on the type of receiver and on the application (e.g. movements of the platform). Furthermore, the dependence of each metric with the position error is dependent on the type of receiver so that the classification thresholds need to be adopted carefully.