## 4 Experimental Results and Analysis
### Establishment of PLS Prediction Model for Mineral Content of Lunar Regolith
The predicted and measured values of six major minerals of lunar regolith are evenly distributed along the y = x line. Table 1 gives the root mean square error (RMSE) and correlation coefficient of the predicted and measured content of the six major minerals in lunar highland, and evaluates the accuracy of the PLS model. The correlation coefficients between predicted and measured  
Figure 5: (**a–f**) are respectively the prediction of mineral content of volcanic glass, agglutinate, ilmenite, plagioclase, pyroxene, and olivine of lunar highland from the experimental group and their comparative analysis with the measured mineral contents. contents of the six major mineral are all greater than 0.99. The smallest RMSE is 0.0386 for ilmenite and the largest is 1.5440 for plagioclase. The overall model has a good simulation effect. Based on the PLS method and the measured spectra data, the inversion of mineral content of lunar highland can be realized. Regarding to the mineral content retrieval of lunar mare, 18 randomly selected samples from 27 mare samples were used to model the spectra and mineral content of lunar regolith by PLS method, as shown in Figure 6. The mineral contents of volcanic glass (Figure 6a), agglutinate (Figure 6b), ilmenite (Figure 6c), plagioclase (Figure 6d), pyroxene (Figure 6e), and olivine (Figure 6f) in the lunar regolith were optimized and retrieved, and compared with the measured mineral contents in the lunar regolith. Figure 6 shows that the PLS model has a good simulation effect. As described as Figure 5, this calculation is done for all grain size range, it is combined from all grain sizes. The mineral content of lunar regolith retrieved from mare samples can be linearly fitted with the measured mineral content of lunar regolith. The predicted and measured values of six major minerals of lunar regolith are evenly distributed along the y = x line. Table 2 gives the root mean square error (RMSE) and correlation coefficient of the predicted and measured content of the six major minerals in lunar mare, and evaluates \begin{table}
\begin{tabular}{l c c c c c c} \hline  & **Volcanic Glass** & **Agglutinate** & **Ilmenite** & **Plagioclase** & **Pyroxene** & **Olivine** \\ \hline Correlation Coefficient & 0.9963 & 0.9928 & 0.9967 & 0.9940 & 0.9950 & 0.9986 \\ RMSE & 0.1716 & 1.4305 & 0.0386 & 1.5440 & 0.5550 & 0.0588 \\ \hline \end{tabular}
\end{table} 
Table 1: Evaluation of prediction accuracy of mineral content of lunar highland from the experimental group. Figure 6: (**a–f**) are respectively the prediction of mineral content of volcanic glass, agglutinate, ilmenite, plagioclase, pyroxene, and olivine of lunar mare from the experimental group and their comparative analysis with the measured mineral contents. the accuracy of the PLS model. The largest correlation coefficients between predicted and measured contents of the six major mineral is 0.9964 for volcanic glass, and the smallest is 0.9340 for plagioclase. The smallest RMSE is 0.3122 for ilmenite and the largest is 1.2640 for agglutinate. The overall model has a good simulation effect. Based on the PLS method and the measured spectra data, the inversion of mineral content of lunar mare can be realized.