Development and assessment of a medium-range real-time kinematic GPS algorithm using an ionospheric information filter

The key requirement of centimeter-level real-time kinematic (RTK) positioni ng using the Global Positioning System (GPS) relies on the ability to fast and accurately determine the ambiguities of carrier-phase observations to t heir inherent integer values. In addition, the identification must be compl eted on the fly since the remote receiver is constantly in motion. The Kalm an filter-based algorithm described in this paper uses an ionospheric infor mation filter to perform on-the-fly phase ambiguity resolution for high pre cision RTK applications. Experiments based on 16 independent test baselines ranging from 10-50 km in length indicate that the algorithm can reliably a chieve centimeter-level positioning accuracy, provided that a small enough threshold value for ambiguity identification is pre-defined and that suffic ient geometry change in the GPS constellation is observed. Experimental res ults also show that the convergence (initialization) time for ambiguity res olution is linearly proportional to instantaneous baseline length, and the slope of the regression line increases with tighter ambiguity identificatio n criteria.