## 5 Results
### Indoor and Outdoor Continuous Elastic Navigation and Positioning Test  
The elastic PNT positioning terminal developed by the State Key Laboratory of Satellite Navigation System and Equipment (as shown in Figure 2) is used to test the navigation and positioning performance in indoor and outdoor complex environments.  
Firstly, the navigation and positioning performance of the proposed algorithm under fine motion is tested in the indoor open area. The test results are shown in Figure 7.  
Figure 5: Combined positioning of Wi-Fi/Bluetooth and inertial sensor in indoor strip.  
Figure 6: Navigation and positioning of outdoor satellite navigation differential enhancement and 5G combination.  
Figure 7 shows that in the indoor open area, the motion trajectory of the algorithm proposed in this paper forms a complex Chinese character. From the comparison between the motion trajectory and the background pattern in Figure 7, it can be seen that the motion trajectory and the background font pattern almost coincide, indicating that the algorithm proposed in this paper has high navigation and positioning accuracy in the indoor open area and can distinguish the subtle differences of the motion trajectory.  
The performance of the algorithm proposed in this paper can be better verified under the dynamic condition of multiscene switching. Therefore, the multiscene switching dynamic positioning experiment is carried out in the indoor and outdoor environments of the artificial intelligence test field of the State Key Laboratory of Satellite Navigation System and Equipment. The test environment includes the indoor and outdoor environments, indoor narrow areas and indoor open areas. The test results are shown in Figures 8-10.  
In this test, the tester took the multisource elastic fusion positioning terminal from outdoors to indoors, passing through the outdoor area, indoor narrow areas and open areas. It can be seen from Figure 8 that the final trajectory can be in accordance with the figure on the ground.  
Figure 9 shows that after the tester goes from the outdoors to the indoor narrow area, the indoor open area and then to the indoor narrow area, goes out of the room and returns to the starting point, the whole motion track is completely closed.  
Figure 10 shows test personnel go from indoors to outdoors, starting from the indoor open area, passing through the indoor open area, the indoor long and narrow area, the outdoors, the indoor long and narrow area and the indoor open area to realize the complete closure of motion estimation.  
Figure 10: Third test.  
Figure 9: Second test.  
From the dynamic test results in Figures 8-10, it can be seen that the navigation and positioning performance of the algorithm proposed in this paper is independent of the starting point position and can realize continuous and seamless navigation and positioning in complex and changeable environments.  
Table 2 shows the average positioning accuracy of three dynamic tests in Figures 8-10.  
As can be seen from Table 2, the positioning accuracy of the three dynamic tests is better than 0.7 m. Compared with the static environment, the positioning accuracy is poor because the whole trajectory involves a variety of indoor and outdoor complex scenes and involves the adjustment and switching process, which affects the overall positioning performance. The navigation and positioning performance of the algorithm proposed in this paper can meet the current needs of high-precision indoor and outdoor navigation and positioning and has good stability. The positioning is relatively smooth in the scene-switching process without large jumps.