## 4 Image Quality Assessment Results  
In this study, we first extracted the impulse response function (IRF) of seven flexible CRs from SAR images and then evaluated the image quality of C-SAR/01 using spatial resolution, peak sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) [2; 24; 25; 26]. Spatial resolution is an important index for evaluating the ability of images to distinctly distinguish ground point targets, and it is usually expressed as IRW, which is the width between the \(-3\) dB points on the impulse response function (IRF) main lobe peak [2], as shown in Figure 9, including resolution in range direction \(\rho_{r}\) and azimuth direction \(\rho_{a}\). The specific calculation formula of resolution in range direction \(\rho_{r}\) is [27]:  
\[\rho_{r}=\frac{c}{2f_{s}Lsin\theta}N_{r} \tag{9}\]  
where \(c\) is the speed of light, \(f_{s}\) is sampling rate, \(L\) is the interpolation multiplier, and \(N_{r}\) is the distance of points between the points with intensities 3 dB below the maximum intensity of main lobe peak in range direction IRF, and \(\theta\) is the radar beam incidence angle. Figure 9: Schematic of IRF. The specific calculation formula of resolution in azimuth direction \(\rho_{a}\) is [27]:  
\[\rho_{a}=\frac{V_{g}}{f_{p}L}N_{a} \tag{10}\]  
Here, \(V_{g}\) is the velocity of the beam center pointing to the ground, \(f_{p}\) is the pulse repetition frequency, \(L\) is the interpolation multiple, and \(N_{a}\) is the distance of points between the points with intensities 3 dB below the maximum intensity of main lobe peak in azimuth direction IRF. PSLR is defined as the ratio of the highest intensity of the sidelobe to the peak of the main lobe in the point target IRF [2]. This is illustrated in Figure 9 and calculated in Equation (11). The PSLR describes the extent at which the weakly scattering point is masked by the strong scattering point [26]. \[\mathrm{PSLR}=10 lg\frac{I_{s}}{I_{m}} \tag{11}\]  
Here, \(I_{s}\) represents the highest intensity of the sidelobe, and \(I_{m}\) represents the peak intensity of the main lobe. ISLR is defined as the ratio of the total energy in sidelobes to the main lobe energy on the point target IRF, as calculated in Equation (12). The ISLR measures the energy spilled from the main lobe to the sidelobe [26]. \[\mathrm{ISRL}=10 lg\frac{E_{S}}{E_{M}} \tag{12}\]  
Here, \(E_{S}\) represents the total energy of the sidelobes; \(E_{M}\) is the energy of the main lobe, while \(E_{S}\) and \(E_{M}\) is calculated as:  
\[E_{s}=\int_{-\infty}^{a}\lvert h(r)\rvert^{2}dr+\int_{b}^{\infty}\lvert h(r) \rvert^{2}dr \tag{13}\]  
\[E_{M}=\int_{a}^{b}\lvert h(r)\rvert^{2}dr \tag{14}\]  
where the area within the integration limit \((a,b)\) corresponds to the main lobe region, and the area outside \((a,b)\) corresponds to the sidelobe region as the junction between the main lobe and the sidelobe. CRs are usually visualized as dots or small crosses in SAR images. Interpolation is often employed to distinctly characterize point targets and their surrounding pixel points, so as to ensure accurate characterization, as well as measure their performance metrics. In this study, 8-fold fast Fourier transform (FFT) interpolation [23], which ensures both the computational efficiency and accuracy of results, was adopted to finely characterize CR impulse response within the 32 \(\times\) 32 integration window obtained by the sliding window-based integral method. FFT interpolation is achieved mainly by one fast Fourier transform and one fast Fourier inverse transform, and its operation is divided into three main steps. Firstly, it involves computing the FFT of the original sequence \(x(n,n)\) in \(N*N\) size, as shown in Equation (15). Additionally, it involves constructing a new sequence \(X_{M}(k_{1},k_{2})\) in length \(M*M\) by \(X_{N}(k_{1},k_{2})\), as shown in Equation (16). After that, it requires the performing of an inverse FFT of the sequence \(X_{M}(k_{1},k_{2})\) to obtain \(\hat{x}(m,m)\), as shown in Equation (17).