# LSOS: An FG Position Method Based on Group Phase Ranging Ambiguity Estimation of BeiDou Pseudolite
## 4 Implementations and Evaluation  
### Real Measurement Analysis  
In this section, we use the existing BeiDou pseudo-satellite test environment to analyze the ranging and positioning performance in large-scale space. In this paper, B1I (1561.098 MHz) and B2I (1207.14 MHz) are selected to broadcast the signals in the indoor  
Figure 4: The algorithm processing block diagram.  
Figure 3: The factorial optimization model architecture for BDAPS.  
first floor hall. The location test terminal selects the time-space box location terminal which is developed by our project group based on ublox commercial chip. The data collection and display software adopts the integrated indoor and outdoor positioning APP of BeiDou. At the same time, in order to further analyze the positioning accuracy of the algorithm in this paper, the dynamic camera is selected as the location comparison benchmark. The dynamic camera can achieve real-time positioning accuracy to the millimeter level after calibration, which can meet the requirements of accuracy evaluation in this paper. The specific test scenario is shown in Figure 5. The top is the BDS pseudo-satellite positioning network, the equipment on the black shelf in the middle is the dynamic camera system, and the bottom is the positioning test service equipment that we use. The open area in the middle of the site is our actual test area. The test area has been built with accurate 3D modeling and ground test map, which can meet the needs of various test types.  
Here we first broadcast the dual-frequency pseudo-satellite signal by BDAPS and validate the algorithm for the ranging capability in wireless environment. The observation information of carrier phase at 21 and 26 positions is collected for ranging analysis. As you can see from Figure 6, there is an estimation error of about one cycle in the estimation of carrier phase integer for two frequency points in the same channel, which can be up to two cycles in the previous test.  
Figure 5: Test scenario.  
The positioning performance of the algorithm is further analyzed in this paper. During the testing process, the space-time box terminal and the dynamic capture positioning rigid body are placed near each other, and the data of the two positioning modes are collected at the same time. In order to facilitate analysis, this algorithm is represented by FG-GPRE. Here, we show the position map of two groups of motion. The detailed analysis results are as follows.  
According to the test results in Figure 7, the proposed algorithm can locate continuously and does not appear the phenomenon of location hops affected by cycle slips. According to the above data, the location accuracy is further analyzed here. According to Table 3, the location ME is 17.16 cm, the location RMSE is 8.6 cm, and the maximum location error is 39.72 cm.  
Figure 6: The estimation of carrier phase integer for two frequency points.  
Figure 7: The first group of positioning accuracy comparison test.  
On the basis of the previous step, the accuracy of the positioning process is further verified here. In the same area, we have completed two rounds of dynamic positioning tests. The test results are shown in Figure 8. It is found that the two-loop trajectories obtained by the proposed algorithm are approximately coincidental and have the same positioning deviation as the reference trajectories. Although the algorithm proposed in this paper has a certain location error in the location accuracy, the location stability is improved significantly. Comparing with the literature 22, it has a better location performance. The positioning accuracy is also analyzed here. According to Table 4, the positioning ME is 20.86 cm, RMSE is 8.6 cm, and the maximum positioning error is 43.99 cm.