053 - Real-time Big Data Processing for GNSS Integrity

053 - Real-time Big Data Processing for GNSS Integrity


Different user communities defines and adopts their specific PNT integrity concepts. The relevance of GNSS integrity is evolving and increasing to support the most sophisticated PNT solutions in different market segments.

Today, a number of GNSS integrity concepts is in use (e.g. RAIM, SBAS) or under development (ARAIM). Yet, all existing integrity concepts have important limitations to protect users in specific local environments. Techniques like RAIM and ARAIM have limitations in harsh local environments, as performance is very sensitive to the loss of tracking of satellites by the user. SBAS techniques are less sensitive to the loss of tracking, but they do not provide integrity information related to the local user environment.

The above limitations have triggered reflections for an innovative solution, here proposed as “Real-time Big Data Processing for GNSS Integrity”.In this concept, user receivers provide data to a Central Processing Facility (CPF). The CPF uses these data to compute not only global integrity products (overbounding satellite orbit and clock errors) but also local ones (overbounding local errors, e.g. multipath, interference, ionosphere).

On the one hand, it is recognized that the typical quality of user receiver data is lower than the one from fixed integrity monitoring stations, like SBAS RIMS data. On the other hand, the number of GNSS-users is significantly higher than the number of fixed integrity monitoring stations (billions of GNSS-users in the world versus 50 RIMS maximum for a typical SBAS infrastructure). From preliminary analyses, it seems that this very large amount of user data can provide integrity products of very high quality, with the additional feature of computing local integrity products.

Therefore, the main objective of the proposed activity is to demonstrate the feasibility of a new concept to compute global and local integrity data in real time based on big-data collected form GNSS user receivers. This concept may be of interest for various user-groups for integrity applications well beyond civil aviation.

The tasks to be performed include:

  • development of prototype CPF algorithms based on user data;
  • simulation of data in various scenarios, e.g. large number of user receiver data with unknown user position and with varying level of multipath and signal blockage;
  • assessment of the need to maintain a very small number of fixed integrity monitoring stations (e.g. to detect common mode failures);
  • computation and trade-off of global and local integrity products;
  • preliminary selection of communication channels and assessment of impact on performance (e.g. Time-To-Alarm, availability).

The main results of the activity will provide:

  • a feasibility assessment of this new integrity concept based on real time processing of big data from a multitude of GNSS user receivers;
  • comparative analysis of benefits and drawbacks, trading off this new concept with existing ones, as SBAS and RAIM, or under development, as ARAIM.