# Bounding Volume Hierarchy-Assisted Fast SAR Image Simulation Based on Spatial Segmentation
## 4 Discussion of Simulation Results
### Analysis of Simulation Results
The flight deck is also arranged with multiple catapults, flame arresters, and dihedral angle structures, displaying some sporadic bright spots. The dihedral scattering between the sea surface and the carrier's side occurs on the edges of the ship. For the flight deck of the ship 1 carrier, the head geometry is obviously elevated, the local incidence angle becomes smaller, and the position shows slightly brighter. The ship 4 is relatively small in size, the tower geometry is stepped, the backscatter is stronger, and the amplitude is brighter. The simulation time consumption of the test is detailed in Table 6, and the comparison results with the CPU single-threaded simulation time consumption are given. The overall simulation details are more realistic and consistent with the microwave scattering theory, which can effectively verify the effectiveness of the proposed method. Figure 11: Comparison between simulation result and real SAR image of Japanese helicopter carrier. Figure 12: Composite model and lattices of sea surface and multi-ships. (**a**) Multi-ships models. (**b**) Composite model of the sea surface and multi-ships. (**c**) Latticed radiation area of the composite model. In order to further verify the generality of the proposed method, the simulation test on a small airplane target is added. As shown in Figure 14a, we select the Quest Kodiak 100 model (the model size is 11 \(\times\) 14 \(\times\) 5 m, the number of surface facets is 13,765). The test selects the parameters in Table 1 (No. 1). The simulation results are shown in Figure 14b. Comparing the simulation results with the real SAR images, the distribution of geometric and radiometric features is still approximately the same. The main reasons for the amplitude differences in local details are as follows. (1) The geometric and material parameters of the constructed target model have errors with the real target; (2) some system parameters of the open dataset are unknown, which are different from the parameters in Table 1 used in the test; (3) and the specific position of the target model with respect to the scene center is shifted from the real situation, and there is a difference in the local incidence angle. Comprehensively analyzing the simulation time in Tables 4, 6 and 7 shows that the proposed method can effectively improve the simulation efficiency of SAR images. After a comprehensive comparison and analysis of the above comprehensive test results, it can be fully proved that the proposed method can effectively improve the simulation efficiency under the premise of ensuring the fidelity of SAR simulation images. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**SAR Image Size (HH)**} & \multirow{2}{*}{\begin{tabular}{c} **Lattice** \\ **Number** \\ \end{tabular} } & \multirow{2}{*}{**CPU Time**} & \multirow{2}{*}{**GPU Time**} & \multirow{2}{*}{\begin{tabular}{c} **Speedup** \\ **Rate** \\ \end{tabular} } \\ \hline \begin{tabular}{c} Composite \\ model of \\ the sea and \\ ships \\ \end{tabular} & \
\begin{tabular}{c} Azimuth \\ Range \\ \end{tabular} &
\begin{tabular}{c} 1021 \\ samples \\ 1319 \\ samples \\ \end{tabular} & 3,928,125 & 242.51 h & 0.92 h & 263.6\(\times\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Time consumption. Figure 13: Simulation results of the composite model of the sea surface and ships.