# Passive Detection of Low-Altitude Signal Sources Using an Improved Cross-Correlation Algorithm
## 4 Performance Results
### Outdoor Experiments
#### 4.1.1 Outdoor Passive Detection of a Low-Altitude Signal Source  
The data was obtained on a bridge in Jimo, Qingdao, in a region with dimensions 1000 m \(\times\) 4500 m \(\times\) 200 m. A dataset refers to the data acquired during one rotation of the receive antenna. The normalized time-frequency matrices after filtering are given in Figure 6 for different distances between the UAV and receiver. These results show that the power of the received signal decreases with distance, as expected. In the experiments, the time that the signal source appears, the direction of arrival, and the start frequency used for communication differ depending on the distance. For outdoor distances of 500 m, 1000 m, 1500 m, 2000 m, 2500 m, and 3000 m, the actual directions of arrival are 85.815\({}^{\circ}\), 95.196\({}^{\circ}\), 98.27\({}^{\circ}\), 99.43\({}^{\circ}\), 37.035\({}^{\circ}\), and 37.642\({}^{\circ}\), respectively. The actual start frequencies are 2.401758 GHz, 2.401758 GHz, 2.401758 GHz, 2.401758 GHz, 2.471992 GHz, and 2.471992 GHz for the same distances from 500 m to 3000 m, respectively. The false alarm probability refers to the percentage of signals incorrectly classified as a UAV being present. Conversely, the missing alarm probability refers to the percentage of signals incorrectly classified as a UAV not being present. In total, 3000 datasets were obtained from the outdoor experiments. Figure 7 presents the false alarm probability and missing alarm probability for different numbers of datasets and different outdoor distances. This shows that for 1500 datasets, the false alarm probabilities are 0.0678 and 0.0527 for the AM and proposed method, respectively. Figure 7b shows that at a distance of 2000 m, the missing alarm probabilities are 0.1275 and 0.0431 for the AM and proposed method, respectively. The missing alarm probability increases with distance, as expected. These results indicate that the proposed algorithm has better performance than the AM. The results for the improved cross-correlation method at different outdoor distances are given in Figure 8. This shows that the cross-correlation is larger in the target area compared to where there is just noise and clutter. Figures 9 and 10 present the frequency and DOA estimation results for several outdoor distances obtained using the proposed method. The frequency estim  
Figure 6: Normalized time–frequency matrices after filtering at outdoor distances of (**a**) 500 m, (**b**) 1000 m, (**c**) 1500 m, (**d**) 2000 m, (**e**) 2500 m, and (**f**) 3000 m.  
Figure 7: (**a**) The false alarm probability for different numbers of outdoor datasets, and (**b**) the missing alarm probability for different outdoor distances. AM: advanced method. Parameter estimation for low-altitude signal sources has not yet been considered in the literature. Thus, two common parameter estimation methods are employed here for comparison with the proposed algorithm. The results with the HOC method [29] for different outdoor distances are given in Figure 11. The position of the maximum value is used as the frequency estimate and the DOA. The estimation accuracy is very poor for distances greater than 1500 m. Figure 12 gives the results for the CFAR method [28] at different outdoor distances and shows that the performance with this method is poor for long distances. Figure 11: The results for the higher-order cumulant (HOC) method outdoors at distances of (**a**) 500 m, (**b**) 1000 m, (**c**) 1500 m, (**d**) 2000 m, (**e**) 2500 m, and (**f**) 3000 m.  
Figure 10: The DOA estimation results using the proposed method outdoors at distances of (**a**) 500 m, (**b**) 1000 m, (**c**) 1500 m, (**d**) 2000 m, (**e**) 2500 m, and (**f**) 3000 m.  
The estimated frequency, direction of arrival, distance, SNR, and maximum improved cross-correlation for the proposed method are given in Table 1. The maximum cross-correlation without a UAV present is much lower than when a UAV is present. When the UAV is present, the maximum cross-correlation and SNR decrease with distance.