# Data Interpretation Technology of GPR Survey Based on Variational Mode Decomposition
## 5 The Analysis of Real Exploration GPR Signals  
The Yunnan Province of China plans to build a highway through a mining area and the project required a geophysical survey. The detection device used was a GSSI SIR-3000 GPR. The central frequency of the antenna was 100 MHz. The length of the detection section was 15.0 m and acquisition space interval was 0.050 m. The cross section had 300 trace records, with each trace containing 512 sampling points. Figure 14a shows the survey records of the GPR.  
Figure 12: Frequency division section based on EMD: (**a**) frequency division section at 1.0 GHz; and, (**b**) frequency division section at 1.2 GHz.  
Figure 13: Frequency division section based on EEMD: (**a**) frequency division section at 1.0 GHz; and, (**b**) time-frequency spectrum at 1.2 GHz.  
Based on the original records of the field (Figure 14a), the mining area was not clear enough. The detection data was processed using VMD Time Frequency in order to test VMD's effect. During processing GPR data, there are several processing steps that are applied. Firstly, the preprocessing of original GPR data is performed to improve the observation of embedded cavities in the radargrams. Mean denoising is used for filtering random noise, and removing DC is used for decreasing the direct current effect. Secondly, every trace time domain data was decomposed by VMD into the IMFs after the preprocessing. Subsequently, the analytic signal was constructed using Hilbert transformation that is based on IMFs, and the instantaneous frequency and amplitude was obtained at every trace. Finally, the Hilbert spectrum of every trace was integrated, and the time-frequency spectrum of the detection signal was obtained while using the proposed method. The 3D GPR data can be sliced on frequency division plane at 80 kHz. Figure 14b shows the frequency division section of the signal at 80 kHz.  
In Figure 14b, it can be seen that there were obvious anomalies that were located in the survey line at 4.5 m, which are obviously different from other regions. The region with anomalies is displayed within elliptic area in Figure 14b. It is a verified fact that there were caverns at the 4.5 m location of the survey line and 7.0 m in depth after drilling. In Figure 14b, the quality of the data section is significantly improved when compared with Figure 14a. The non-uniformity recognition of the medium with the time frequency section is more distinct than the original time domain section. The local anomaly features are highlighted, and the goat is clearly visible from the time frequency section. In Figure 15, frequency division sections at 80 kHz were also obtained with EMD and EEMD. However the region with anomalies does not display well when comparing with Figure 14b. VMD is also better than the other two methods in application. The evidence proves that the proposed method has significant applicability for processing GPR signals.  
Figure 14: Real world GPR data and frequency spectrum: (**a**) time domain GPR record data; and, (**b**) frequency division section at 80 kHz.  
Figure 15: Frequency division section with EMD and EEMD: (**a**) Frequency division section at 80 kHz with EMD; and, (**b**) Frequency division section at 80 kHz with EEMD.