Global Precise Multi-GNSS Positioning with Trimble CenterPoint RTX

Mid of 2011 Trimble introduced the CenterPoint RTX real-time positioning service providing cm-accurate positions for real-time applications. This service targets applications in the precision markets like Precision Agriculture, Survey, Construction and relies on the generation of precise orbit and clock information for GNSS satellites in real-time. The CenterPoint RTX satellite corrections are generated with data from Trimble's world-wide tracking network, consisting of approximately 100 reference stations globally distributed. While the system initially was introduced supporting GPS and GLONASS satellites, recent developments have led to the inclusion of additional navigation satellites. The orbit estimation in the CenterPoint RTX system is based on a combination of a UD-factorized Kalman filter estimating satellite position, satellite velocity, troposphere states, integer ambiguities, solar radiation pressure parameters, harmonic coefficients, and earth orientation parameters. The prediction step in the filter is using a numerical integration of the equations of motion in connection with a dynamic force modeling. Forces considered in the approach are the earth's gravity field, lunar and solar direct tides, solar radiation pressure, solid earth tides, ocean tides, and general relativity. In the RTX orbit processing carrier phase integer ambiguities are resolved in real-time. Also, the satellite orbit states are truly estimated in real-time and continuously adapted over time to better represent the current reality. This means that the satellite positions that are evaluated by the user have prediction times of no more than a few minutes since the last orbit processing filtering update, providing negligible loss of accuracy. The RTX real-time orbit components have a typical overall accuracy of around 2.5 cm considering IGS rapid products as truth. Satellite clock estimation is an essential part of the CenterPoint RTX system. It plays a fundamental role on positioning performance due to a number of reasons. Satellite clocks map directly into line-of-sight observation modeling, yielding into a one to one error impact from clocks into GNSS observables modeling. Due to the same strong relationship, it is of fundamental importance that clocks are generated in a way to facilitate ambiguity resolution within the positioning engine. The processing speed of a clock processor is also of fundamental importance, due to the fact that any delay in computing satellite clocks is directly translated into correction latencies when computing real-time positions on the rover side. For that matter one should keep in mind that regardless how late satellite corrections get to the GNSS receiver in the field, positions have to be provided to the user as soon as the rover GNSS measurements are available. Therefore latencies typically introduce errors into the final real time position. In this paper we define real-time positioning as the computation of positions at the time when the rover observables are available, regardless the latency of the correction stream. This is a necessary concept in order to support dynamic rover GNSS positioning. Clock estimates accuracy is typically of 2 cm or better, latencies of correction signals in CenterPoint RTX are typically below 7 seconds when received at the users GNSS positioning system. The paper describes the technical aspects of the inclusion of the additional satellites in the orbit and clock estimation process and GNSS receiver positioning engine, as well as the respective improvement in the overall system quality caused by the use of the additional satellites. The paper also describes aspects of the methodology applied in the multi-system orbit and clock estimation and validation procedure. Achieved orbit and clock accuracies over a longer time span are demonstrated and discussed. It is shown that cm-accurate results are achieved with the RTX technology presented.