# Passive Detection of Low-Altitude Signal Sources Using an Improved Cross-Correlation Algorithm
## 4 Performance Results
### Outdoor Experiments
#### 4.1.2 Outdoor Passive Detection of Multiple Low-Altitude Signal Sources  
In order to evaluate the ability of the proposed method to detect multiple UAVs simultaneously, the outdoor experiment was repeated using two Phantom 4 Pro UAVs, \(u1\) and \(u2\). The UAVs hovered at the same distance, but with different angles. The normalized time-frequency diagrams after filtering are shown in Figure 13 for different outdoor distances between the UAVs and receiver. For distances of 500 m, 1500 m, and 2500 m, the actual directions of the arrival and start frequencies of \(u1\) were 97.905\({}^{\circ}\), 2.421484 GHz; 112.52\({}^{\circ}\), 2.421484 GHz; and 80.55\({}^{\circ}\), 2.421484 GHz, respectively. The actual directions of the arrival and start frequencies of \(u2\) were 124.92\({}^{\circ}\), 2.471758 GHz; 47.71\({}^{\circ}\), 2.471758 GHz; and 130.05\({}^{\circ}\), 2.471758 GHz for the same distances of 500 m, 1500 m, and 2500 m, respectively.  
The results for the improved cross-correlation method at different outdoor distances are shown in Figure 14 and indicate that two UAVs can be simultaneously detected successfully. The DOA and start frequency estimates for \(u1\) were 98.347\({}^{\circ}\), 2.421445 GHz; 113.242\({}^{\circ}\), 2.421426 GHz; and 79.402\({}^{\circ}\), 2.421436 GHz for distances of 500 m, 1500 m, and 2500 m, respectively. The DOA and start frequency estimates for \(u2\) were 125.865\({}^{\circ}\), 2.471701 GHz; 48.263\({}^{\circ}\), 2.471680 GHz; and 129.465\({}^{\circ}\), 2.471802 GHz for distances of 500 m, 1500 m, and 2500 m, respectively. The corresponding performance with the HOC and CFAR methods is shown in Figures 15 and 16, respectively. Table 3 shows the outdoor parameter estimation errors for the two UAVs using the three methods. For \(u1\), the frequency errors were 0.039 MHz, 3.613 MHz, and 2.732 MHz at a distance of 500 m for the proposed, HOC, and CFAR algorithms, respectively. For all distances, the DOA estimation error was within 3\({}^{\circ}\) using the proposed method. This indicates that this method is able to accurately detect multiple low-altitude signal sources.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Method**} & **500 m** & **1000 m** & **1500 m** & **2000 m** & **2500 m** & **3000 m** \\ \hline \multirow{2}{*}{CFAR} & Error (MHz) & 0.621 & 0.815 & 1.049 & 1.347 & 38.752 & 39.891 \\  & Error (\({}^{\circ}\)) & 7.02 & 0.878 & 2.16 & 2.588 & 13.793 & 5.198 \\ \hline \multirow{2}{*}{HOC} & Error (MHz) & 5.751 & 6.631 & 6.035 & 25.937 & 41.590 & 41.713 \\  & Error (\({}^{\circ}\)) & 6.143 & 3.015 & 0.855 & 47.07 & 11.205 & 4.478 \\ \hline \multirow{2}{*}{Proposed} & Error (MHz) & 0.018 & 0.012 & 0.006 & 0.024 & 0.007 & 0.011 \\  & Error (\({}^{\circ}\)) & 4.405 & 0.618 & 2.18 & 1.6 & 0.605 & 0.708 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameter estimation errors for UAV detection using three methods in an outdoor environment. CFAR: constant false alarm rate; HOC: higher-order cumulant.  
Figure 13: Normalized time–frequency diagrams after filtering for two UAVs outdoors at distances of (**a**) 500 m, (**b**) 1500 m, and (**c**) 2500 m.