## 3 Results
### Flight Detection Experiment  
The field experiment was carried out in two modes: when the unmanned helicopter was in motion and when it was hovering. In the motion mode, we controlled the unmanned helicopter to launch into the air, move back and forth within a range of 200 m at a certain speed. During the flight, we observed whether the spectrometer could work normally and checked the image and spectral data received by the ground computer. In the hover mode, the FTIR system detected and identified SF\({}_{6}\) gas at a distance of 200 m. First, the unmanned helicopter was controlled to collect multiple background spectra around the SF\({}_{6}\) gas release location and store them, and then the SF\({}_{6}\) gas was released from the pressure vessel. According to the visible light camera image, the unmanned helicopter was controlled to aim at the gas release area, collect spectral data and identify the target gas composition. Figure 8a shows the picture of the system ready to fly after the ground installation of the test site and Figure 8b shows the picture of the system in the air. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Specification** \\ \hline Product model & HuaYi UH1C100B, (HuaYi Shenzhen, China) \\ Max speed/(km/h) & 800 \\ Payload/kg & 40 \\ Duration of Flight/h & 1.5\%30 kg \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters of unmanned helicopter. Figure 7: Ammonia gas feature extraction result based on RPCA (red). In the first mode, we powered on the system, opened the instrument control software, and connected the lower computer to communicate with the ground system. We controlled the unmanned helicopter to launch into the air, and increased its speed gradually to 30 km/h. The results of the ground display system show that the unmanned helicopter airborne FTIR remote sensing system can withstand the vibration and other effects of the helicopter during flight and accurately restore the spectrum. When the flight speed reached 30 km/h, the remote data transmission module and the whole system could work normally. In the second mode, the temperature of the experimental flight site was 22.6 \({}^{\circ}\)C, the crosswind speed was 5.6 m/s, and the unmanned helicopter hovered at a height of 20 m above the ground. SF6 gas was released at a distance of 200 m from the hovering point of the drone. The system continuously collected spectral data and identified gas components. The original interferogram data were stored in the memory of the lower computer, and the spectra and identification results were transmitted to the ground control terminal for real-time display. The interface of the host computer for real-time identification of SF6 gas using the FTIR system is shown in Figure 9.  
The FTIR system continuously collected data, and the recovered spectral data are shown in Figure 10. The bold red line is the target spectrum of SF6 gas absorption characteristics, and the rest are multiple background spectra collected near the detection area. As can be seen in Figure 10, noise is introduced into the background spectrum because the unmanned helicopter cannot maintain an absolutely immobile state when hovering in the air. In addition, the fast wind speed in the experimental environment and the rapid change of atmospheric turbulence also made the single background spectrum difficult to be well estimated using prior knowledge. Figure 8: SF6 remote detection experiment carried out by unmanned helicopter airborne FTIR system. (**a**) Unmanned helicopter airborne FTIR system in standby mode on the ground; (**b**) unmanned helicopter airborne FTIR system in the air. Figure 9: SF6 gas identification host computer software interface. The gas feature extraction results are shown in Figure 11, in which Figure 11a shows the differential spectrum of directly subtracting the background spectrum from the target spectrum and Figure 11b shows the RPCA method result.