A grid-based ionospheric weighted method for PPP-RTK with diverse network scales and ionospheric activity levels

Abstract

The performance of precise point positioning real-time kinematic (PPP-RTK) is closely tied to the accuracy of atmospheric corrections, with the ionospheric delay, including its uncertainty, being of particular importance. In this study, a grid-based slant ionospheric weighted method is proposed to enhance PPP-RTK performance across diverse network scales and ionospheric activity levels. First, the receiver-specific hardware delays are precisely calibrated for the maximum utilization of ionospheric corrections retrieved in PPP-RTK networks. Then, a grid-based polynomial fitting and residual interpolation model is developed with a stochastic model considering the distribution of reference stations, the elevation of satellites, and rate of total electron content index (ROTI). Three networks situated in different latitudes with the max inter-station distance of 26.7 km, 134.2 km, and 247.9 km, respectively, were employed to verify the enhancement to PPP-RTK. The proposed method presents a significant improvement in reducing the convergence time of PPP-RTK in all three networks, with the horizontal convergence time decreased from 5 to 14 s to less than 1 s in the small- and medium-scale networks, 44–25 s in the large-scale network compared to the modified linear combination method (MLCM). Besides, a vehicular experiment on an urban loop was conducted for further validation. The positioning accuracy of the PPP-RTK vehicular solutions with the newly proposed method is 2.74, 2.28 and 5.54 cm in the east, north and up components, respectively, with an improvement of 10, 11 and 40% over MLCM. The proportion of 3D positioning accuracy less than 5 cm also increased from 50.1 to 87.8%. Moreover, during the ionospheric active period, the average positioning accuracy is increased from decimeter- to centimeter-level horizontally, and the fixing rate can be increased from 80.6 to 90.0%.