GNSS – Multi-Signal / Multi-System Model with Raw Approach

System of multiple GNSS
System of multiple GNSS (copyright: ESA).

Processing only single- or dual-frequency signals from the GPS constellation currently still is the standard for Global Navigation Satellite System (GNSS) applications. However, the on-going modernization of the existing systems GPS (USA) and GLONASS (Russia) and the upcoming completion of the new systems Galileo (Europe) and Beidou/Compass (China) lead to a huge increase in the number of GNSS satellites in view and the number of signals/frequencies available to the users.

This development will in future offer a number of benefits both to fundamental science and (commercial) positioning, navigation and timing users, whereas it also introduces a number of challenges which have not yet been solved. These challenges for example include the fundamental question of how to jointly process the observations from multiple frequencies and satellites of different GNSS constellations to achieve the best solution for a certain application.

The standard GNSS signal processing approaches currently used worldwide do not offer the possibility to simultaneously process multi-frequency signals from multiple GNSS to benefit for example from the increased signal quality of some of the new signals. At the institute of physical and satellite geodesy (PSGD) we therefore use a new method called “GNSS Raw Observation Approach” [1] in cooperation with the Navigation Support Office at ESA/ESOC (European Space Operation Centre) in Darmstadt.

In the raw observation processing approach neither differences nor linear combinations of GNSS observations are formed and all available pseudo range and carrier phase observations on multiple frequencies can be jointly processed. This allows for example to benefit from the low code noise of the Galileo E5 AltBOC signal.

Reference (Ph.D. thesis at PSG):

[1] Schoenemann, E. (2013), Analysis of GNSS raw observations in PPP solutions. Schriftenreihe der Fachrichtung Geodäsie (42). Darmstadt ISBN 978-3-935631-31-0