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(This is a work in progress, so it is changing all the time, this notice will be removed once the document is complete)

C4G launches C4Gnet.XYZ in January 2018 and this launch has so many important advancements bundled into it that there is too much to give all the details in the RTN User Guide. In this article we will try to give you all the verbose information on the tools and features that are all rolled up into the C4Gnet.XYZ RTN launch.

First a little background information on the very important change to C4Gnet.XYZ. 

C4G originally made the switch to using RTN.LSU.EDU as our RTN host address years ago to provide a robust failover method that allows RTN users to be directed to any of our servers without having to make any changes in their rover settings. We have a network of high availability firewalls, load balancers and database servers that are monitored for quality of services and weighting and direct clients accordingly to the best services dynamically. This makes the C4Gnet very reliable and is only possible when clients use the host address RTN.LSU.EDU. This DNS or Domain Name System was based on the top level DNS of LSU.EDU and worked perfect for years until LSU made a change to new tools to manage DNS for the LSU.EDU top level domain. This change required the DNS RTN.LSU.EDU to be pointed to a single IP address removing the ability for C4G to redirect the DNS RTN.LSU.EDU dynamically! The only way to fix this was to get a new DNS that was not connected to the top level DNS, LSU.EDU, so C4G acquired the domain C4Gnet.XYZ in an effort to restore our robust dynamic failover capability.

  • C4Gnet.XYZ restores our High Availability Always On robust failover ability and we encourage all clients that can use DNS Host Addresses in their rover setups to do so!

With this launch the LSU Center for GeoInformatics introduces the long awaited Trimble Pivot Platform software package version 3.10.x

New features deployed in this software release include the following:

  • C4Gnet GNSS Online Post Processing
  • VRS iScope 
  • iScope Live!
  • Real Time RTXnet Processor using Precise Point Positioning (PPP)
  • New mountpoint naming convention 
    • New PPP Mountpoints 
    • Multi-Reference Frame Support
    • GNSS Galileo Support


RTX Technology

The RTX Technology infrastructure is a unified framework for estimating satellite parameters for any GNSS satellite. GNSS field receivers use advanced Precise Point Positioning (PPP) processing algorithms to combine RTX corrections with local measurements and produce cm level accurate absolute positions.

RTXNet Processor

RTX Technology enables the RTXNet Processor to develop corrections for a full range of satellite systems and delivers Network-RTK corrections for GPS, GLONASS, BeiDou, Galileo, and QZSS. Using a PPP mountpoint gives rovers a second real-time method to collect data and as a real-time way to check data collected with a real-time VRS RTK mountpoint. If data collected with both PPP and RTK agree, you have a very high confidence that the data collected is accurate.

Dynamic Station Coordinates

Dynamic Station Coordinates eliminate the negative effects of erroneous coordinates on RTKNet/RTXNet Network processors performance. This gives the motors behind these tools the following benefits:

  • Improved network processor performance.
  • Improve rover position performance.

The “Dynamic Station Coordinates (DSC) approach” uses “Trimble RTX™” technology to compute the so-called “Dynamic Station Coordinates” for each reference station. These coordinates are dynamically re-computed and updated to best fit the reference stations’ position. DSC is designed to automatically avoid the influence of biased position information during Network-RTK positioning. With the Dynamic Station Coordinates (DSC) approach, local coordinates are not used to initialize the network processor. Reference Station Coordinates in ITRF2008 Current Epoch are directly estimated by using GNSS data with Trimble RTX™ technology. For each epoch, the internally computed RTX position is fed into two Kalman filters, one configured to expect no movement (static) and the other for sudden movement. The static filter outputs the highest accuracy position, but has a substantial reaction delay to position changes. The sudden movement filter has a fair accuracy and reaction time to movement. By comparing the position from the static and sudden movement filters, unexpected movements of the station can be determined. Converged position information from the static filter will only be forwarded into the processors. In case of movement detection, no data from the affected station will be processed until the accuracy of the position is below the default thresholds.