# Time-Frequency Attribute Analysis of Channel 1 Data of Lunar Penetrating Radar
## 3 Results
### CEEMD of the Trace at N104  
In terms of the N104 trace, CEEMD is performed (Figure 7). The noise standard deviation is set to be 0.2. The number of realizations is 200 and the maximum number of sifting iterations allowed is 200. The N104 trace is divided into seven IMFs and one residual.  
After decomposing the trace at N104, in order to observe the time-frequency information of the data in each component, we performed a short-time Fourier transform for each component (Figure 8). Analyze each component one by one:  
1. In the STFT spectrum of the IMF1 component, energy is concentrated mainly at 150 MHz, and a small amount of energy is at 100 and 60 MHz; this component can be considered a high-frequency noise component.
2. In the STFT spectrum of the IMF2 and IMF3 components, the main energy is collected near 60 MHz, and some of the energy scattered around it is considered to be the component containing the useful signal.
3. The main energy in the STFT spectrum of the IMF4 component is collected near 30 MHz, which is considered to be a lower-frequency noise component.
4. Among the IMF components, IMF5 is worthy of attention. Two obvious energy information are observed from the component curve (in the IMF5 curve in Figure 7) and its STFT spectrum (Figure 8e), which are around 3500 and 5800 ns, respectively. The reflection of these two positions was used for reflection in the articles by [PERSON] et al. [6] and [PERSON] et al. [10], but it can be seen from the STFT spectrum that the frequency is between 10 and 15 MHz, and it is quite different  
Figure 6: (**a**) LPR CH-1 overall data and (**b**) stagnation points’ traces after gain.  
from the center frequency of the transmitter. [PERSON] et al. also used the S transform and LPR ground data to verify the trap of these two pitfalls [20]. In summary, the IMF5 component is considered to be the unusable component.
5. The STFT spectra of IMF5, IMF6, and IMF7 and the residual component show that the energy is collected below 10 MHz, which is a low-frequency unwanted component.  
Figure 8: Time-frequency spectrum of each intrinsic mode function (IMF) decomposed from the trace at N104. (**a**) IMF1. (**b**) IMF2. (**c**) IMF3. (**d**) IMF4. (**e**) IMF5. (**f**) IMF6. (**g**) IMF7. (**h**) Residual.  
Figure 7: Analysis of the trace at N104 by complete ensemble empirical mode decomposition (CEEMD).  
On the other hand, from the Hilbert spectrum of IMFs at N104 (Figure 9), it can be seen that the energy in the shallow part is mainly distributed in the low-frequency IMF components below 20 MHz. The deep part mainly includes three parts, a high-frequency IMF component of 150 MHz, an IMF component of 60 MHz, which is consistent with the transmission frequency, and a low-frequency pitfall component of 20 MHz or less. Here again, an aliasing component around 3500 and 5800 ns can be found.  
After decomposing and analyzing the single trace at N104 as an example, we perform CEEMD on all CH-1 data (Figure 10) and the traces of stagnation points (Figure 11) in order to obtain a deeper understanding and utilization of the CH-1 data.  
After comprehensively observing the CEEMD components of the overall CH-1 data and the CEEMD components of the stagnation points' traces, it can be found that in IMF5 (shown by the arrows in Figures 10 and 11), two pitfalls at 3500 and 5800 ns can be found (IMF5 in the stagnation points' traces is more obvious than IMF5 in the overall CH-1 data).