# An Efficient Single-Anchor Localization Method Using Ultra-Wide Bandwidth Systems
## 5 Experiment and Analysis
### Performance Evaluation
#### 5.2.1 Static test point
However, the CIR of the anchor is only 1016 nanoseconds long, thus the number of agents that can be simultaneously localized is limited in order to avoid overlap of the responses of different agents. Figure 7: An illustration of the received CIR at the anchor from three agents’ Resp messages. We introduce an individual delay \(\delta_{1}=0\) ns, \(\delta_{2}=150\) ns, and \(\delta_{3}=300\) ns so that the pulses can avoid overlap and avoid strong multipaths. To quantify the overall localization performance of the system, we analyze the statistical characteristics of the localization error based on the CDF. Figure 5b shows the performance comparison when using SAL-Normal and the proposed SAL method with \(N_{\text{a}}=3\). When using SAL-Normal, the system can reach a 90% error of 20.6 cm and a median error of 10.3 cm. When using the proposed SAL method, a 90% error and median error of 23.4 cm and 10.5 cm are achieved, respectively. The results show that the performance of the proposed method can almost reach the traditional method. In order to validate our localization system in other environments, we have selected a smaller lab classroom (E2) with a CAD map shown in Figure 6a. The size of the room is about 6 m \(\times\) 8 m = 48 m\({}^{2}\), with more desks, cabinets, chairs, and other reflection objects and scattering objects. As shown in Figure 6a, we randomly selected \(N_{t}=14\) test points and performed \(N_{m}=1000\) measurements at each test point. As in the previous experimental approach, we evaluate the performance of the system using SAL-Normal and the proposed SAL method, respectively. The results show that the estimated position is close to the ground truth, and the performance is better when using SAL-Normal. Figure 6b shows the CDF comparison when using different localization methods in E2. When using SAL-Normal, a 90% error of 13.8 cm and median error of 6.7 cm are achieved. When using the proposed SAL method, the 90% error is 16.8 cm and the median error is 7.5 cm. The conclusion of the experiment is similar to that in E1. The results also show that the performance in the lab classroom is better than in the hall. This is because the test points we select in the classroom are closer to the anchor, and the localization error caused by the AOA estimation error is smaller. In addition, the increase in reflectors and scatterers has little effect on the localization performance, thanks to the existence of LOS propagation. To further analyze the source of the localization error, we analyzed the ranging error and angle estimation error of three agents in both scenarios. Specifically, the mean of distance measurement error is less than 10 cm, the standard deviation of the distance measurements is 3.2 cm, the mean of angle estimation error is less than 2 degrees, and the standard deviation of the angle measurements is 3 degrees. Therefore, when the agent is far away from the anchor, i.e., 2 m away, the angle estimation error is the main source of localization error. As the distance increases, the angle estimation error will introduce a larger localization error, which can be improved by increasing the antenna number. To evaluate the localization performance for different number of agents, we employ \(N_{\text{a}}=1,2,3\) agents in both E1 and E2. The 90% and median localization error with different agent number in the two test environment is shown in Tables 1 and 2. In both tables, the results show that when using SAL-Normal, the overall localization performance does not increase with the number of agents. When using the proposed SAL method, the localization accuracy will decrease slightly with the increase of the agent number. Also, we find that the localization accuracy of two agents and three agents is similar when using the proposed SAL method, which shows our method will not be fragile in multi-agent scenarios. In general, our method is a little bit worse than the normal method in terms of positioning accuracy, but it can achieve decimeter-level localization accuracy, which is enough for practical use.