## 3 The Proposed Multiple-Signal Joint Estimation Method
### Square Root Unscented Stable Filter
Furthermore, a Square Root Unscented stable filter is proposed to guarantee positive estimation-error covariance and avoid the divergence of fusion positioning results caused by abnormal observation data

Figure 8: GNSS-5G hybrid positioning with severe occlusion. (**a**) Sky plot (**b**) Taylor diagram. since the square root of the covariance with stabilized coefficient rather than the covariance itself propagates. Finally, comprehensive simulations are carried out to evaluate regarding the measurements' estimation error and positioning error under different conditions. It is obvious that the proposed SRUSF method substantially enhances the positioning accuracy and reliability compared with the five multiple-signal joint estimation methods. Especially in the scene with moderate occlusion, the RMSE of SRUSF is 18% higher than that of the suboptimal algorithm. ## 6 Conclusions

In this study, we sought to provide a GNSS and 5G signal joint processing method in support of the general applicability of a highly dependable spatio-temporal network. The proposed approach exhibits considerable promise for multiple-signal joint estimation. This paper will provide significant assistance for highly dependable PNT services for mass users under the GNSS-and-5G-based spatio-temporal network architecture. In the future, we will start from the mass-scale application of the integration of the GNSS and 5G mobile communication network, considering the credibility of positioning results provided via the novel spatio-temporal network, to further improve the precision, availability, and dependability of the PNT service. However, a field test still needs to be carried out in the actual environment in the future. In addition, although the errors caused by multi-type and multi-scale signal switching are considered in this paper, more complex error models and suppression methods can be studied in the future to further improve the receiver's robustness to unknown errors. Conceptualization, Z.D. (Zhongliang Deng) and Y.H. ; methodology, J.L. and E.H.; software, J.L. ; validation, J.L., X.D., Z.Z., Z.D. ([PERSON]) and E.H.; formal analysis, J.L. and Y.H. ; investigation, [PERSON] ([PERSON]) and B.L. ; resources, J.L. and Z.Z. ; writing--original draft preparation, J.L. and E.H.; writing--review and editing, J.L. and Z.D. ([PERSON]); visualization, J.L. ; project administration, [PERSON] ([PERSON]) and Y.H. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Key Research and Development Program of China (grant number: 2022 YFB3904702 and 2022 YFB3904603), and the National Natural Science Foundation of China under Grants: 6220020330. The data that support the findings of this study are available from the corresponding author upon reasonable request. The authors declare no conflict of interest. ## References

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