## 5 Experimental Results
### Simulation Experiment  
* **Point target**  
Firstly, the effectiveness of the algorithm is verified by the simulation of a single scattering point target. The simulation parameters are shown in Table 2. At \(t_{a}=0\), the position of the target is at the center of the scene, and the coordinate is \(P_{0}(0,5000)\). This paper is mainly aimed at the ground vehicle target. In a synthetic aperture time, it can be considered that the motion characteristics of the scattering points of each part of the target are the same [32]; that is, the speed and acceleration of each part are the same, and there is no rotational motion. Rotating target detection and parameter estimation can be found in the literature [33; 34]. The target trajectory after range compression is shown in Figure 5a. It can be seen from the figure that the target trajectory has serious range migration caused by the target movement. After Hough-SOKT and third-order term migration correction, the DCCF constructed by the proposed method is shown in Figure 5b, the target energy is corrected for the same range cell. However, the peak position of the DCCF constructed by KT-CICPF is shifted by the range cell, and its peak energy is dispersed into three range cells, as shown in Figure 5c. The reason for this problem is the coupling between DCCF and the range migration caused by insufficient range migration correction, which directly affects the extraction of the chirp signal of Equation (24). The DCCF after third-order correction is shown in Figure 5b. The amplitude and Doppler spectrum of \(S_{5}(t_{m})\) extracted by the two methods are shown as Figure 5d,e. It can be seen that the amplitude gain of the signal extracted by the proposed method is stronger and the Doppler spectrum is smoother, which conforms to the ideal chirped signal. However, the amplitude and Doppler spectrum extracted by KT-CICPF fluctuate greatly. Figure 5f,g show the \(F_{0}\)-\(F_{1}\) parameter plane constructed by the two methods. Inside the red rectangle is a local magnification of the peak position. Figure 5h shows the slice along \(F_{1}\) in the \(F_{0}\)-\(F_{1}\) plane. It can be clearly seen that the peak of the parameter plane constructed by the proposed method is more significant, while the parameter plane generated by KT-CICPF is energy-dispersive. Figure 5i,j show the imaging results of the two methods, respectively. Figure 5k,l are slices of the imaging results in the range direction and azimuth direction. It can be seen from the figure that the proposed method has a better focus. However, in the contrasting method, the target occupies multiple range cells due to the residual range migration, which reduces the resolution of the target. The parameter estimation results obtained by the two methods are shown in Table 3. It can be seen that the parameter estimation accuracy of the proposed method is relatively high, while the parameter error estimated by KT-CICPF is relatively large. Especially for the estimated value of \(a_{2}\), the error of the KT-CICPF method reaches 7.01%, while the maximum relative error of the parameters estimated by the proposed method is only 0.21%. Therefore, it can be concluded that the proposed method has better parameter estimation performance. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Value** & **Parameter** & **Value** \\ \hline Carrier frequency & 10 GHz & Range sampling frequency & 2000 MHz \\ Platform velocity & 100 m/s & Pulse duration time & 1 \(\mu\)s \\ Range bandwidth & 1000 Mhz & Center slant range & 5 Km \\ Pulse repetition frequency & 1200 Hz & Synthetic aperture time & 5 s \\ \(v_{r}\) & 3 m/s & \(a_{r}\) & \(-1\) m/s\({}^{2}\) \\ \(v_{x}\) & 4 m/s & \(a_{x}\) & \(2\) m/s\({}^{2}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameter. In addition, the focusing performance of the moving target is shown in Table 4. The theoretical range resolution is \(0.886(c/2B)=0.1329\) m. According to Equation (5),