## 6 Conclusions  
In this paper, we propose an indoor and outdoor multisource fusion navigation and positioning algorithm based on particle filters. According to the navigation and positioning requirements of indoor and outdoor complex scenes, this method uses a variety of sensor information to construct a multisource elastic fusion positioning model, eliminates abnormal positioning results according to the previous moment's positioning results and carrier motion state and calculates the centroid of the remaining multisource sensor positioning results. With consideration of the results from different sensors and the accuracy of different sensors, it shows that: the weights of different sensor results are given to achieve the flexible fusion localization of multisensor simultaneous interpreting.  
The test environment is built in the artificial intelligence test field of the State Key Laboratory of Satellite Navigation System and Equipment, and the multisource elastic fusion positioning terminal developed by the State Key Laboratory of Satellite Navigation System and Equipment is used to test and verify the positioning performance of the method proposed in this paper. The test results show that the proposed algorithm can solve the problem of seamless navigation and positioning under the condition of indoor and outdoor multiscene switching. The elastic fusion positioning accuracy is better than 0.7 m, and the positioning stability is good. There are no jumps in the positioning results in the three tests.  
This paper proposes an algorithm to solve the problem of indoor and outdoor high-precision seamless navigation and positioning continuity. The redundant information of elastic multisource sensors is used to improve the robustness of navigation and positioning in complex and changeable scenes. In the future, it can be applied to positioning and navigation, personnel management, safety rescue and other aspects in complex urban scenes, promote the all-round development of the indoor positioning blue ocean market and finally realize the seamless integration of the indoor and outdoor interconnection of all things.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Path of Particle** & \multicolumn{3}{c}{**Average Positioning Error/m**} \\ \hline \multirow{2}{*}{1} & \multirow{2}{*}{shown in Figure 8} & X & 0.4161 & \multirow{2}{*}{0.6372} \\ \cline{3-3} \cline{5-5}  & & Y & 0.4826 & \\ \hline \multirow{2}{*}{2} & \multirow{2}{*}{shown in Figure 9} & X & 0.4322 & \multirow{2}{*}{0.6697} \\ \cline{3-3} \cline{5-5}  & & Y & 0.5116 & \\ \hline \multirow{2}{*}{3} & \multirow{2}{*}{shown in Figure 10} & X & 0.4704 & \multirow{2}{*}{0.6846} \\ \cline{3-3} \cline{5-5}  & & Y & 0.4974 & \\ \hline \hline \end{tabular}
\end{table}
Table 2: Average positioning error of dynamic test.  
**Author Contributions:** All authors contributed to the manuscript and discussed the results. All authors together developed the idea that led to this paper. [PERSON] and [PERSON] conceived the experiments and analyzed the data. [PERSON] provided critical comments and contributed to the final revision of the paper. [PERSON] contributed to the expression and the design of programs. [PERSON] wrote the manuscript and all the authors participated in amending the manuscript. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported in part by the National Key Research and Development Plan of China (project: Intelligent Emergency Rescue Equipment Platform Technology and Equipment: No. 2019 YFC1511500 and Indoor Hybrid Intelligent Positioning and Indoor GIS Technology: No. 2016 YFB0502100).  
**Data Availability Statement:** Not applicable, the study does not report any data.  
**Conflicts of Interest:** The authors declare no conflict of interest.