# A Study on a Radio Source Location Estimation System Using High Altitude Platform Stations (HAPS)
## 4 Conclusions  
In this study, we compared the HAPS, UAV, and DEURAS systems for the location estimation of radio sources, and found that the HAPS estimation showed excellent accuracy at distances up to 20 km due to its high LoS ratio, while the UAV estimation showed poor performance due to interference from reflected waves, especially in urban environments. The position estimation using an antenna configuration that mimics the DEURAS system also showed lower position estimation accuracy compared to the HAPS due to the antenna  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Beamformer** & **MUSIC** \\ \hline Mean error [m] & 150.7 & 151.6 \\ \hline CDF90\% [m] & 186.0 & 186.1 \\ \hline Detection percentage [\%] & 98.7 & \\ \hline \hline \end{tabular}
\end{table}
Table 10: Results with the HAPS 500 m away.  
Figure 20: CDF of errors for different sensor altitudes with sensor radius of 500 m.  
height and reflected waves. Overall, the HAPS is excellent for monitoring radio sources over a wide area, and we believe that integrating the HAPS into the existing DEURAS setup has the potential to enhance the current system.  
However, several problems are expected to arise when the HAPS is actually used for location estimation in practice. The first is the coordination among three HAPS units. The DEURAS system uses a wide-area cabled LAN to aggregate information from each receiving antenna at the center station, but it is considered difficult to use this method for the HAPS since wired backhauling is impossible for aerial stations. However, such issues can be solved via wireless or optical backhauling among HAPS units, or by using feeder links to coordinate with other HAPSs via ground antennas. The second is the case where there are multiple sources of emitters in the same service area. As a first step to demonstrate the benefit of the proposed system, this paper assumed only a single source. But in realistic circumstances, there could be multiple sources emitted at the same frequency and time due to the nature of illegal emitters. In such a case, the HAPS units need to identify multiple sources simultaneously. This issue can also be solved via sharing the antenna resources equipped on the HAPS units. The third is when the illegal emitter is not fixed is but moving like a car or a truck. In such case, the introduction of a tracking filter upon the mechanism in this paper might be a solution. Although we have not yet been able to study these issues in depth, they will all be considered for our future works.  
Furthermore, we used MATLAB to simulate the location estimation of a radio source. It is possible that diffracted and scattered waves, in addition to other arriving and reflected waves, may exist in a real environment, and these may affect the estimation results. Therefore, we would like to conduct actual experiments in the future to confirm the accuracy of the estimation. In addition, we would like to consider the location estimation of low-power radio sources, moving radio sources, and indoor radio sources, which were not covered in this study.  
Conceptualization, G.K.T.; Methodology, G.K.T.; Software, Y.F.; Validation, Y.F.; Investigation, Y.F.; Data curation, Y.F.; Writing--original draft, Y.F.; Writing--review & editing, G.K.T.; Supervision, G.K.T. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
Not applicable.  
Data Availability Statement: Data is contained within the article.  
The authors declare no conflict of interest.