# LaRaWAPS: A Wide-Area Positioning System Based on LoRa Mesh
## 6 Evaluation
### Positioning Experiment  
Based on the previous steps, this section evaluates the positioning performance of the system.  
In the experiment, a total of 9 LoRa anchor points were placed in a square area with a side length of 500 m. The locations of the anchor points were determined according to the proposed anchor point deployment algorithm. Nine anchor points were networked by wireless mesh, 30 different positions of the target were located in the region and the positioning errors were recorded. The bandwidth, spread factor, and other parameters of the system are the same as those of the ranging experiment. We compare the mainstream LoRa positioning system, which uses all anchor points for position calculation [24]. The cumulative distribution function of positioning errors is shown in Figure 12.  
In Figure 12, the red line represents the positioning error of LoRaWAPS, with an average error of 14.49 m and 70% of the errors being less than 20 m. The blue line corresponds to the positioning error of the system in reference [24], with an average positioning error of 33.93 m. Thanks to the improvement of the ranging algorithm and positioning algorithm, LoRaWAPS shows better positioning performance. However, there is still quite a large area  
Figure 11: CDF of range algorithm.  
Figure 12: CDF of localization algorithm.  
of poor signal quality due to the occlusion of buildings, trees, and vehicles, leading to low ranging and positioning accuracy (larger than 10 m).  
To investigate the effect of the density of LoRa anchor points on positioning performance, 18 anchor points are deployed in the same square area with a side length of 500 m to achieve better signal coverage. Other settings are the same as in the previous experiment. The cumulative distribution function of positioning error for different anchor point densities is shown in Figure 13.  
In Figure 13, the red lines represent the positioning errors of the system when 18 anchor points are deployed. The average positioning error is less than 5 m, and the maximum positioning error is less than 10 m. Considering that the positioning error with civil GPS as a reference is about 5 m, it can be considered that the positioning capability of the proposed system is close to GPS when the deployment density of anchor points is high.  
Finally, system-level experiments were conducted to prove that all parts of the system can run smoothly. We have deployed LoRaWAPS in the Yuquan Campus of Zhejiang University, with a total of 21 anchor points, covering an area of approximately 0.25 km\({}^{2}\) within the campus. The experimental area where we collected data is surrounded by buildings that are mostly below 50 m in height. In order to evaluate the real-time positioning accuracy of the LoRaWAPS, the presenter moved freely within the campus with a target node and a mobile phone with satellite positioning capability. The mobile phone recorded the GPS coordinates in real time and uploaded them to the server. LoRaWAPS located the target node through anchor points and uploaded the location results to the server as well. The presenter can access the server via a web page to compare the GPS positioning results with LoRaWAPS positioning results in real time. The web page is shown in Figure 14.  
In Figure 14, blue circles represent LoRaWAPS location results and black circles represent GPS location results. At the bottom of the map, time, position coordinates calculated by LoRaWAPS, anchor numbers involved in positioning in LoRaWAPS, ranging results of each anchor, and position coordinates provided by GPS, are displayed successively in real time. It can be seen that in most cases, the positioning error of LoRaWAPS is within 15 m. This accuracy is acceptable for most IoT location scenarios. If higher positioning accuracy is needed, simply increase the density of anchor deployment in exchange for better signal coverage.  
Figure 13: Influence of anchor density on positioning ability.