# A Novel Cross-Correlation Algorithm Based on the Differential for Target Detection of Passive Radar
## 3 Result
### Measured Data, Measured Results, and Analysis
#### 3.2.2 Measured Results and Analysis of the FM Signal  
The effective bandwidth of the FM signal was within 75 kHz, the carrier frequency was 96.1 MHz, and the sampling frequency was 200 kHz. A total of seven frames of data were collected, and the length of each frame was 2 s. The target parameters were [336 km, \(-\)282.3 km/h] and [394 km, 64.1 km/h]. In the simulation, the data in the first frame were randomly selected and the accumulation times were 0.5 s and 1 s, respectively. Similar to audio signal data, FM signal data has many clutters with Doppler spread in the area close to the receiver and the target in the Doppler dimension will be covered by near-field clutter. Thus, only the distance dimension simulation results are given below.  
It can be seen from Figure 20a,b that the output SNR of the target increases with the different accumulation time. When the accumulation time was 0.5 s, the traditional  
Figure 19: Integration results obtained with proposed method for the audio signal: \(N=2\times 10^{5}\); (**a**) Doppler dimension; (**b**) Range dimension.  
Figure 18: Integration results obtained with the proposed method for the audio signal: \(N=10^{5}\); (**a**) Doppler dimension; (**b**) Range dimension.  
R-D output SNR of the two targets was about 4.5 dB and 0.8 dB, respectively. When the accumulation time was 1s, the traditional R-D output SNR of the two targets was about 5.9 dB and 2.5 dB, respectively. The improvement of output SNR in R-D processing is about 1.4 dB and 0.7 dB.  
It can be seen from Figure 21a,b that when the accumulation time was 0.5 s, the two target output SNRs of the algorithm were about 15 dB and 1.6 dB. The output SNR was increased by about 10.5 dB and 0.8 dB, respectively, compared with the traditional R-D processing method in Figure 20. When the accumulation time was 1 s, the output SNRs of the two targets were about 23 dB and 9 dB, respectively, and the output SNR increased by about 16.1 dB and 6.5 dB compared with the traditional R-D processing method in Figure 20b.  
When the accumulation time is short, the accumulation gain of this algorithm is higher than that of the traditional R-D algorithm. However, because the output SNR of the algorithm in this paper can be able to improve more for large targets, small targets will be affected by the sidelobe of large targets in short accumulation time accumulation, resulting in limited improvement. However, when the accumulation time increases, the output SNR of the algorithm is improved faster. Therefore, as shown in Figure 21a,b, when the accumulation time is twice the original time, the output SNR of the target in Figure 21b is  
Figure 21: Integration results obtained with the proposed method for the FM signal: (**a**) \(N=10^{5}\); (**b**) \(N=2\times 10^{5}\).  
Figure 20: Integration results with traditional R-D processing for the FM signal: (**a**) \(N=10^{5}\); (**b**) \(N=2\times 10^{5}\).  
about 12.5 dB and 8 dB higher than that in Figure 21a, while the traditional R-D algorithm, as shown in Figure 20a,b, is only about 1 dB higher (theoretically, the maximum increase can be about 3 dB).