## 5 Simulation and Experimental Results  
### Point Target Simulation  
We conducted point target simulation for non-uniform sampling in THz SAR based on the imaging geometry shown in Figure 7. The radar parameters used are consistent with the 300 GHz stepped frequency radar system employed in the experiment, as shown in Table 1. Simulating the point target \(B\) in Figure 7, we assume that the azimuth position of \(B\) is \(x_{B}=4\) m and \(R_{B}=4\) m. The main simulation parameters are provided in Table 2.  
According to the antenna beamwidth, the radar is able to effectively receive the echo data of point target \(B\) within the azimuth position range of [3.7729 m, 4.2271 m]. We conducted a simulation by randomly sampling within this range, generating echo data corresponding to the positions obtained through random sampling. We selected three sets of non-uniformly sampled echo data. The value of \(N_{m}\) for these three sets are 150, 200, and 250, respectively, approximately 1.2, 1.6, and 2 times the number of the azimuth wavenumber spectrum to be estimated. Figure 8 shows the sampling point positions for these three sets of echo data. The vertical axis represents the non-uniformly sampled positions in azimuth, and the horizontal axis represents the index \(i\). A noticeable trend is that with a smaller value of \(N_{m}\), the interval between these points becomes relatively larger, leading to a more uneven distribution of the obtained echo data. \begin{table}
\begin{tabular}{c c} \hline \hline Parameters & Value \\ \hline Frequency step size & 18 MHz \\ Total radar bandwidth & 28.8 GHz \\ Azimuth beamwidth & 6.5\({}^{\circ}\) \\ Antenna aperture & 1 cm \\ Transmitting power & 0.5 mW \\ \hline \hline \end{tabular}
\end{table} 
Table 1: 300 GHz radar experimental parameters. \begin{table}
\begin{tabular}{c c} \hline \hline Parameters & Value \\ \hline Number of Frequency steps \(N_{k}\) & 1601 \\ Radar center frequency \(f_{c}\) & 300 GHz \\ Slant range of scene center \(R_{c}\) & 4.167 m \\ Azimuth beam width \(\theta_{bw}\) & 6.5\({}^{\circ}\) \\ Squint angle \(\theta_{0}\) & 0\({}^{\circ}\) \\ Range resolution \(\rho_{k}\) & 0.0052 m \\ Azimuth oversampling factor \(a\) & 1.2 \\ Azimuth wavenumber bandwidth \(K_{\text{max}}\) & 136.158 m\({}^{-1}\) \\ Azimuth wavenumber spectral interval \(\Delta k\) & 2.2013 m\({}^{-1}\) \\ Number of Azimuth wavenumber spectrum \(2M+1\) & 125 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Main simulation parameters for non-uniform sampling of point target \(B\). Figure 7: Flow chart of SAR imaging algorithm combining Tikhonov regularization and RDA. We compared the proposed algorithm (TR-RDA) with RDA, the Azimuth Resampling Algorithm (AR-RDA) based on spline interpolation and BPA. Figure 9 shows the imaging results for the three sets of echo data. For the convenience of comparison, the results were normalized and displayed in logarithmic form, with the image range set to be above \(-30\) dB. When RDA is directly applied to the azimuth non-uniformly sampled echo data, the imaging results showed severe defocusing. The focusing effect of point targets obtained by AR-RDA deteriorates as the value of \(N_{m}\) decreases due to the influence of spectral aliasing effects, while the TR-RDA and BPA algorithms exhibit relatively minor variations with changes in \(N_{m}\). Moreover, from the imaging results, it is evident that the TR-RDA algorithm yields superior focusing effects compared to the results obtained by AR-RDA and BPA. Figure 10 shows the azimuth impulse response function (IRF) obtained from the imaging results. Corresponding characteristic parameters for the point target are presented in Table 3. The integration sidelobe ratio (ISLR) obtained by the three algorithms is consistent with the  
Figure 8: Non-uniform sampling position distribution of three groups of echo data. Figure 9: Imaging results of (**a**) RDA, (**b**) AR-RDA, (**c**) TR-RDA, and (**d**) BPA when \(N_{m}=150\).