# ISAR Imaging Analysis of Complex Aerial Targets Based on Deep Learning
## 4 Analysis of Simulation Results and Experimental Results  
### Simulation Results  
The RCS spatial distribution characteristics of complex air targets exhibit the following features: (1) a high RCS value within a narrow airspace; (2) a low RCS value with certain fluctuations across a wide airspace range. Furthermore, due to the aircraft's complex structure and the presence of multiple scattering centers, the different incidence angles of the radar will lead to great changes in the spatial distribution characteristics of the aircraft RCS, as shown in Figure 5[18]. For complex air targets, the scattering centers consist of scatterers with simple geometric structures, such as plates, points, edges, angles, etc. Consequently, complex air targets can be represented as a vector superposition of backscatter from several typical feature directions. The maximum RCS values for these typical feature directions of complex air targets, along with the corresponding contribution positions, are presented in Table 2[19]. Therefore, this paper proposes a simulation scheme focusing on three typical characteristics of complex air targets: the nose, wing and tail directions. The structure diagram illustrating the simulated assembly of each part of the aircraft is presented in Figure 6. A 60\({}^{\circ}\) corner reflector with a side length of 0.6 m, two 60\({}^{\circ}\) corner reflectors with a side length of 0.3 m and two Luneberg lens reflector with a radius of 40 mm can be used as the best design scheme for the typical features of the head in Figure 6a, a combination of four 60\({}^{\circ}\) corner reflectors with a side length of 0.78 m, two metal balls with a diameter of 200 mm, and a flapper with an offset of 50 mm can be used as the best \begin{table}
\begin{tabular}{c c} \hline \hline
**Number of Training data** & 1000 \\ \hline Loss function & Smooth \\ Gradient optimization & Adam \\ Learning rate & 0.002 \\ Batch\_size & 1 \\
**Epoch** & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Training parameters. Figure 5: ISAR imaging of an aircraft. design solution for the typical features of the wing, a 60\({}^{\circ}\) variable corner reflector with a side length of 0.54 m, a metal ball diameter of 80 mm at the top of the left corner reflector, 88 mm at the right reflector and a Luneberg lens reflector diameter of 80 mm are used as the best design scheme for the typical features of the tail. In this paper, the FEKO 2019 is applied to calculate the far-field RCS distribution characteristics of the target. FEKO is a software program for electromagnetic calculation and electromagnetic field analysis, which is widely used in electromagnetic scattering simulation. FEKO has numerous solvers, and the solvers can be selected according to specific simulation requirements. FEKO integrates many methods of electromagnetic numerical calculation, including the Method of Moments (MOM), the Fast Multipole Method (MLFMM), the Ray Tracing Geometrical Optics Method (RL-GO), the Physical Optics Method (PO), the Geometrical Optics Method (GO), the Geometrical Theory of Diffraction (UTD), and the Finite Element Method (FEM). The main steps to solve the RCS distribution characteristics using FEKO are as follows:  
(1) Model establishment. CADFEKO has the function of establishing geometric models. After modeling the model, as shown in Figure 6d, it is imported into FEKO. (2) The relevant parameters, such as the incident wave frequency, angle, phase, polarization mode, and single-station working mode, are set, and then the far-field RCS solver is added. The specific set parameters are shown in Table 3.  
Figure 6: The structure diagram of the simulation assembly of each part of the aircraft. (**a**) Typical head orientation. (**b**) Typical wing simulation. (**c**) Typical tail orientation. (**d**) Aircraft omnidirectional simulation. (3) Select the appropriate algorithm.