Effects of signal distortion biases on atmospheric delay modeling and PPP-RTK in multi-receiver-type regional networks

Abstract Atmospheric delay modeling, comprising both ionospheric and tropospheric delays, is a crucial component for implementing PPP-RTK. Its primary task is to obtain atmospheric delays at the user end through interpolation, and then broadcast them as atmospheric augmented information to users. However, in PPP-RTK systems, multiple receiver types may be used at the server end and user end. In this case, the presence of signal distortion bias (SDB) introduces significant discrepancies between the broadcast atmospheric augmentation information and the actual atmospheric delays at the user end. This prevents users from eliminating interference caused by atmospheric delay, consequently hindering the achievement of rapid ambiguity resolution. To solve this problem, we focus on the PPP-RTK technique in multi-receiver-type regional networks, and establish a PPP-RTK system that takes into account SDB. Firstly, the expression for the impact of SDB on ionospheric delay is theoretically derived, and its magnitude is further assessed. Subsequently, two selected regional networks with multiple receiver types are used for PPP-RTK validation. The results demonstrate that, the ionospheric slant delay error caused by a 1-ns geometry-free combination of the single-differenced SDB is 0.4-0.6 m at f1 frequency, as demonstrated for GPS/Galileo/BDS-3. After SDB correction, the interpolation accuracy of ionospheric slant delay can reach within ±0.1 m, and the SDB-induced decimeter-level jumps between epochs during interpolation can be significantly mitigated. Additionally, SDB correction yields a significant improvement in PPP-RTK positioning performance across regional networks containing multiple receiver types. Specifically, for the user stations from the two selected regional networks, after SDB correction, the positioning error curves for both horizontal and vertical components converge faster. Furthermore, the ambiguity fixing rate can rise by 2.5%-4.9% and 6.9%-14.7%, respectively. Moreover, the time-to-first-fix decreases by 16.9%-35.8% and 31.6%-40.9%, respectively.