Reliable real-time kinematic (RTK) positioning is highly sensitive to short-term ionospheric irregularities and spatial electron density gradients, which may degrade ambiguity resolution and positioning integrity. Existing disturbance indicators typically rely on single-parameter metrics such as the Rate of Total Electron Content (TEC) Index (ROTI) or spatial TEC gradients considered independently, limiting their capability to characterize complex space–time ionospheric dynamics. We introduce a quantile-based composite ionospheric disturbance estimator designed for RTK positioning reliability assessment. The proposed framework integrates temporal ionospheric variability and spatial Vertical TEC (VTEC) gradient information into a unified risk indicator. Short-term ionospheric irregularities are characterized using rolling-median ROTI values, from which a high-quantile regional disturbance metric is extracted. Spatial ionospheric structure is quantified through interpolation of the VTEC field and computation of the gradient magnitude, followed by high-quantile extraction of gradient intensity. Both components are normalized using an adaptive quantile-based scaling scheme to ensure robustness against extreme values and regional statistical variability. The final RTK disturbance estimator is formulated as a weighted composite index combining normalized temporal and spatial disturbance measures. The method is fully reproducible and independent of absolute TEC magnitude, relying solely on GNSS-derived ionospheric observables. Validation using dense multi-frequency GNSS observations demonstrates that the composite estimator captures disturbance patterns not resolved by global ionospheric models and provides a physically interpretable risk score relevant for high-precision GNSS applications. The proposed approach offers a generalizable framework for ionospheric integrity monitoring and composite risk assessment in real-time GNSS positioning systems. The proposed approach provides a reproducible GNSS-based framework for composite disturbance monitoring. In this study, the method is validated using a mid-latitude regional CORS network (Latvia); extension to other ionospheric regimes and sparse networks requires further investigation.
Vallis et al. (Sun,) studied this question.