## 4 Simulation and Experimental Data
### Simulation Data  
We use gprMax software (v3) to build the model of the 3D TWI for a moving target [15]. The model is given in Figure 10a, which is constructed strictly according to the real scene in Figure 10b. The thickness of the wall is 24 cm, and the relative permittivity \(\varepsilon_{1}=6.0\). The radar parameters designed in the simulation are given in Table 1. The array structure of the MIMO radar is given in Figure 5b. In the simulation, the human target is equivalent to a cylinder. The target moves away from the radar at a speed of 0.8 m/s from (0, 0, 4.0 m). Based on the normal direction of the wall, the moving direction of the target is 30\({}^{\circ}\). The 3D imaging, azimuth-range 2D projection, and azimuth-height 2D projection results without compensation are given in Figure 11a-c. The sidelobes in the imaging are high, and the position shows obvious deviation according to the 2D projections of the azimuth range and azimuth height. Figure 11e shows the azimuth-range 2D projection compensated by the RCMCA; the sidelobes of the target are low, and the imaging position is basically close to the starting point (0, 0, 4.0 m). Figure 11g-I are the imaging results after compensation using the algorithm proposed in this paper. The problem of the sidelobes and the position deviation of the target is also well resolved, and the effect has reached the same level as the RCMCA. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Signal & Pulse \\ Center frequency & 1 GHz \\ Bandwidth & 1 GHz \\ Scanning rate & 3 frame/s \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The simulation parameters of the radar. Figure 11: _Cont._  
Figure 10: The scene of the 3D TWI. (**a**) The simulation scene; (**b**) the experimental scene. Figure 12 is the projection comparison of the 3D imaging for the different algorithms in the azimuth and height directions. The sidelobe levels in the azimuth and height directions before compensation are \(-1.3\) dB and \(-6.0\) dB, respectively, and the position deviation levels in the azimuth and height directions are 0.32 m and 0.30 m, respectively. The RCMCA eliminates the sidelobes in the azimuth and height directions, and the position deviations in the azimuth and height directions are 0.06 m and 0.05 m, respectively. The sidelobes in the azimuth and height directions are also basically eliminated after compensation using the proposed method, and the position deviations in the azimuth and height directions are 0.03 m and 0.08 m, respectively, which are basically consistent with the RCMCA. In addition, the simulations are carried out separately for the targets whose velocity is between 0 and 1.8 m/s, and whose distance is between 2 and 9 m. Setting the starting  
Figure 11: The simulation results. (**a–c**) The 3D imaging, azimuth-range (x–z) 2D projection, and azimuth-height (x–y) 2D projection before compensation; (**d–f**) the 3D imaging, x–z 2D projection, and x–y 2D projection after compensation using an RCMCA; (**g–i**) the 3D imaging, x–z 2D projection, and x–y 2D projection after compensation using the proposed method. Figure 12: 1D projection. (**a**) Azimuth projection; (**b**) height projection. point of the target as (0, 0, 4.0 m), Figure 13a shows the positioning deviation (3D positioning deviation) of the targets at different speeds. The position deviation before the motion compensation increases with the moving speed. After the RCMCA or the proposed algorithm, the position deviation is kept within 0.30 m at different speeds. Figure 13b gives the positioning deviation when the target passes through different positions at a speed of 0.8 m/s. The positioning deviation increases with distance without compensation. After being compensated using the RCMCA or the proposed algorithm, the position deviation Is kept within 0.30 m.  
Table 2 shows the performance comparison between the different motion compensation algorithms.