# Low-Altitude Sensing Model: Analysis Leveraging ISAC in Real-World Environments
## 4 Performance Verification and Analysis
### Networked Sensing Validation  
The single base station sensing tests evaluated the performance of individual stations, while the multi-BS networked sensing test delved into the model performance from a wide-area sensing perspective. These tests involved constructing base stations based on a multi-BS cellular-like topology and adjusting relevant parameters to assess the key metrics of the model under networked conditions, focusing on verifying the improvement in single base station sensing blind spots. This provides support for the planning and construction of base station networks. When validating the performance of the multi-BS cellular-like topology sensing model, the first step is to select and construct the ISAC base stations according to the theoretical multi-BS cellular-like topology. This topology achieves continuous sensing at different heights by spatially stretching and translating the traditional cellular communication topology in the vertical dimension, enabling cellular-like networked sensing across horizontal cross-sections at various altitudes. From Section 3, the station spacing \(d\) and the coverage radius \(R\) must satisfy \(d\leq R\) to ensure seamless coverage. On this basis, the sector's normal directions and vertical elevation angles of each station were finely adjusted to align as closely as possible with the theoretical model, ensuring the accuracy of the tests. After completing the base station deployment, the sensing functions of all sectors in the ISAC base stations were activated, constructing a comprehensive multi-BS sensing network. Systematic sensing tests were conducted within the test area under the networked configuration. The UAV was selected as the test target, and tests were performed at 100 m and 300 m above the ground. The UAV fle at a stable speed of 5 m/s along a planned route, which is precisely designed to ensure that the UAV sequentially passed through the coverage areas of each station, thereby comprehensively detecting the sensing performance of the base stations at different locations. To ensure the reliability and representativeness of the test data, each flight height involved repeated traversals of the entire coverage area, with no fewer than 1200 valid sample points collected for each flight height. From the test results (as shown in Figures 15-18), in areas near the Site 1/2/6/7 base stations at various heights, the sensing SNR and accuracy performed well due to the station locations being more aligned with the multi-BS cellular-like topology model. However, in some areas, abnormal sensing accuracy was observed. For example, occasional scattered points with accuracy below the specified threshold were primarily caused by the overlap of the flight route with roads, where reflections from large ground vehicles introduced clutter interference. This interference reduced the sensing SNR, thereby affecting sensing accuracy. Specifically, in the red-circled area near Site 3, the actual construction location of Site 5 significantly deviated from the theoretical model, resulting in the blind spot of Site 3 not being effectively covered by Site 5. This led to a lower sensing SNR in this area, directly causing degraded sensing performance. Moreover, as the height increased, such as at 300 m, the blind spot area became larger than that at 100 m, resulting in an increased increased signal-to-noise ratio of 100 m-SNR. Figure 16: Multi-BS sensing test results at the altitude of 100 m–positioning accuracy. Figure 17: Multi-BS sensing test results at the altitude of 300 m-SNR. Figure 18: Multi-BS sensing test results at the altitude of 300 m–positioning accuracy. Figure 15: Multi-BS sensing test results at the altitude of 100 m-SNR. increased number of points with poor performance. This phenomenon aligned with the theoretical expectations. Further analysis revealed that the distribution trends of accuracy and the SNR were similar. In areas with a lower SNR, the accuracy values are also poorer.