Development of Confidence Bound Visualization Tool for LTE-Based UAV Surveillance in Urban Areas

We have developed a tool to visualize a situation of estimating the positions of unmanned aerial vehicles (UAVs) using long-term evolution (LTE) signals in an urban area. In our visualization tool, true positions of UAVs and evolved Node Bs (eNodeBs), estimated positions of UAVs, and the calculated horizontal and vertical protection levels (HPLs and VPLs) are displayed in a 3D city map. For a realistic simulation, the 3D city map is generated using real buildings and terrain data of Gangnam, Seoul, Korea. Users can directly specify the locations of UAVs and eNodeBs to simulate these cases. Error variances are added to the true range between UAVs and eNodeBs in the developed tool. Next, the position and the HPL and VPL of each UAV are calculated and displayed on the map. Using the developed visualization tool, we observed changes in the estimated positions and confidence bounds of UAVs by adjusting the number of eNodeBs transmitting LTE signals. Simulation results show that the size of confidence bounds decreases as the number of eNodeBs increases.