Accurision develops the GUIDANCE™ solution, a robust, high-precision GNSS code receiver solution for highly automated and self-driving vehicles. The GUIDANCE™ solution makes use of the most advanced civilian GNSS signals, the Galileo E5 AltBOC and the BeiDou Phase 3 B2 signals. To reach the required robustness and the accuracy, the GUIDANCE™ solution will also use the Galileo E6 High Accuracy Service.
One of the main challenges for a robust GNSS solution is its ability to handle interferences in the relevant radio frequencies. Due to its weak transmit power GNSS signals are vulnerable to interferences. These interferences can lead to the disruption of GNSS services.
Therefore, the development, test, and implementation of a software prototype was set as a subtask of the overall R&D plan for our GNSS receiver. This software will offer interference mitigation algorithms in the Galileo E5 frequency band with regards to aviation radio signals like Distance Measurement Equipment (DME) and Tactical Air Navigation (TACAN).
Due to the few scientific papers available describing the real-world implications of these interferers, Accurision hired a third party to be able to detect, classify, and document GNSS interferers. They developed a custom designed DME/TACAN detection and classification system according to Accurision’s requirements for the relevant Galileo frequencies. It is capable of concurrently scanning E1, E5, and E6 frequency bands, detecting interferers and – in case of any interferers present – recording and classifying it for further analysis and playback. The system is designed as a mobile unit, enabling to conduct tests in proximity of DME/TACAN stations and other “suspicious” facilities like air surveillance radar sites.
In addition, we will also run field tests at random points to get an even more complete overview of interferences present in the relevant frequencies. This will allow us to see the effects of the signals of interest on the GNSS system. Furthermore, we will get a good understanding of any additional interferers - intentional or unintentional - present in the relevant GNSS frequency spectrum.
All field tests are documented in a database including meta data and a digitised recording of the interference occurrence. The result will be an ever-growing collection of real-world samples. These samples will serve us to enhance and fine-tune our algorithms for detecting, classifying, and mitigating interferences to improve and strengthen our GNSS receiver. This increased resilience against intentional and unintentional interferences will further bolster the overall system robustness of our GUIDANCE™ GNSS receiver.