The precision of positioning information provided by global navigation satellite system (GNSS) is important for Internet of Things applications in smart cities. Multipath effects, mainly including multipath interference and non-line-of-sight (NLOS) reception, are the main errors that affect the positioning precision. The multipath hemispherical map (MHM) mitigates multipath interference, but NLOS reception is often ignored. In this study, we propose the refined multipath and NLOS hemispherical maps (MNHMs) to mitigate both NLOS reception and multipath interference simultaneously. Specifically, first, NLOS reception and multipath interference are preliminarily separated using the carrier-to-noise density ratio (C/N0) nominal function, and then the NLOS hemispherical map (NHM) is established for the first time, and the MHM is also established; Second, the refined MNHMs are constructed by adjusting and interpolating the grid correction values of MHM and NHM to improve the accuracy and availability; Third, the NLOS reception and multipath interference are corrected simultaneously. To validate the proposed method, two consecutive 48-hour RTK occlusion positioning experiments were carried out. The positioning results show that the positioning precision of the proposed method is improved compared with that of the uncorrected and conventional methods based on MHM. Specifically, the proposed method achieves average reductions of 23.5% and 29.5% in the 2D and 3D root mean square errors, respectively. Meanwhile, the residuals of both datasets show a significant reduction, indicating that the proposed method effectively mitigates multipath and NLOS errors. In addition, a practical observation dataset is used to verify the reliability of the proposed method.
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