Bye-bye, bias! The ESA Multi-GNSS Bias Reference Frame

Differential Code Biases (DCBs) are systematic errors, or biases, between two Global Navigation Satellite System (GNSS) code observations at the same or different frequencies. Knowledge of DCBs is required for positioning of GNSS receivers, extracting ionosphere total electron content (TEC), and other applications. Proper knowledge of DCBs is crucial to many navigation applications but also non-navigation applications such as ionospheric analysis and time transfer. The multitude of new signals offered by modernized and new GNSS constellations, requires a comprehensive multi-GNSS bias product. And because of the multitude of GNSS signals it has become more practical to provide the DCBs, differential signal biases, as observable specific biases, OSBs.

At the Navigation Support Office at ESA/ESOC we have for many years relied on the bias products (DCB and OSB) coming from the CODE analysis centre. But in the fast-developing Multi-GNSS landscape it became clear that we needed to have to capability to generate our own independent bias product. For our different GNSS projects we therefore have developed a process to generate our own OSB product with the ambition to have DCBs for all existing MGNSS signals, as long as the signals are tracked by the stations in the large IGS station network. And rather than monthly biases as typically provided and used within the IGS, we have moved to what we call a “Bias Reference Frame” (BREF). The absolute value is still determined by a zero-mean condition at a certain date. But from that point in time the biases are kept stable unless a clear jump in the satellite bias is, automatically, detected. The detectability is at the 0.25ns for well observed biases. The DCB version of the product is publicly available on our Navigation Office website. The OSB version is still under development and testing.

In developing this product, we found some very interesting features of the biases when looking at the biases of the so called “interoperable” signals, which we will present and discuss. We demonstrate the importance of this product for the analysis of the Sentinel 6A data which tracks Galileo and an interesting mix of GPS signals which makes it hard to process the GPS data with the standard IGS products, in particular for PPP-AR.