The extension of network RTK to larger networks is facilitated by a state-space representation of error sources, and is often associated with the term PPP-RTK. By adding atmospheric (troposphere and ionosphere) corrections to satellite orbit and clock corrections, it is possible to obtain fast convergence and seamless transition from a network RTK to a PPP solution. While this concept has been introduced nearly 15 years ago, there are still very few providers of PPP-RTK services at a global scale. Is this about to change?
The state-space representation (SSR) was introduced by Geo++ as an alternative to the popular observation-space representation used to broadcast dispersive and non-dispersive errors. By using a proper parameterization, it is possible achieve instantaneous cm-level positioning accuracies with SSR corrections computed from a regional network of stations. The Geo++ software is currently being used by several organizations worldwide, with a few of them processing more than a hundred stations. However, all of these networks are independent and do not offer a global demonstration of the concept.
It is also interesting to note that companies operating global networks of receivers are currently not offering a PPP-RTK solution, most likely because they do not have the density of stations needed for this approach. An exception is the Trimble RTX system which offers a 1-5 minute convergence time in a small region of central North America, and in several countries in Europe. I can easily foresee Trimble expanding and other companies following by integrating regional RTK networks into global solutions.
It is likely that global PPP-RTK solutions will first emerge from organizations tapping into publicly available stations since the coverage is quite dense in several regions of the world. The Technical University of Catalonia (UPC), through the European Space Agency, has already obtained a patent on “Fast-PPP” and is well under way into developing an operational real-time 3D ionosphere map allowing for fast convergence of PPP solutions. From an abstract submitted to the ION GNSS+ 2016 conference, it seems like JPL is also interested in fast PPP convergence. They are proposing to use a 3D representation of the ionosphere only to recover unbiased STEC at individual stations, thereby reducing the computational load associated with the 3D model. It will be interesting to see if this feature will only be available in their real-time service or if it will make it into APPS, their post-processing service. Geoscience Australia is also hard at work on a PPP-RTK solution with a possible 3D ionospheric model, although I have few details on the status of their developments.
Last but not least, NRCan is also working on fast PPP convergence on a global level for post-processing purposes. The methodology and some results will be presented in a panel discussion at the ION GNSS+ 2016 conference. Of course, I will make sure to write a blog post on this topic in September: stay tuned!