## 4 Simulation and Test Verification
### Simulated Test
#### 4.1.2 Anti-Jamming Performance Verification  
To verify the performance of the proposed algorithm, comparative tests were conducted under different interference scenarios to evaluate the anti-jamming capabilities. Two interference scenarios were designed with the parameters shown in Table 1. The compared algorithms included: Multi-Scale Short-Time Fourier Transform (MSTFT) [30], Adaptive Wavelet Packet Coefficient Threshold (WPCT) [31], and Time-Domain Joint Fractional Fourier Transform (FrFT) [33]. For MSTFT, three scales were adopted with a pole contraction factor of 0.85 for the 2 nd-order IIR notch filter. For WPCT, the \"Dmey\" mother wavelet function was used with 5 decomposition layers, and soft thresholding was applied for interference detection and cancellation. For FrFT, 2000 scanning points were set to search for the optimal order of interference signals, with parameter estimation performed once per data batch. Figure 7a,b present the normalized mean square error (NMSE) of processed Iridium signals and output signal-to-interference-plus-noise ratio (SINR), respectively, obtained through 50 Monte Carlo experiments under different interference scenarios when the input JSR varies from 5 to 30 dB. Figure 7 shows that the anti-jamming performance of the SAIOR algorithm is generally better than those of the other compared algorithms, and its output  
Figure 6: Change in power spectrum before and after anti-jamming under strong interference for scenario 2 (JSR 25 dB). **(a)** Before anti-jamming. **(b)** The resampled data obtained by optimizing the sampling of the original received signal. **(c)** After anti-jamming. Figure 7: Anti-jamming performance verification of each algorithm under jamming scenarios. **(a)** NMSE of desired signal after interference suppression. **(b)** Output SINR after interference suppression. slowly with the increase in the input JSR, which ensures the successful acquisition of Iridium signals. The performance of SAIOR is superior because it eliminates high-power Iridium signals before optimized sampling to extract PFM interference, removing the impact of Iridium signals on interference detection. The performance degradation with the increase in the interference energy is not significant because the optimized sampling method effectively concentrates interference components into a few frequency points with high aggregation, reducing overlap between desired signals and interference without dispersion as interference energy increases. Notably, SAIOR performs better in Scenario 1 than Scenario 2 because multi-component PFM interference signals with the same carrier frequency are transformed into single-frequency interference after optimized sampling, while those with different carrier frequencies are concentrated into several single-frequency interferences in the new sampled data. The number of single-frequency points depends on the carrier frequency of PFM interference, meaning that, under the same conditions, the overlap between Iridium signals and interference signals in Scenario 2 is greater than in Scenario 1. When interference is removed, Iridium signals overlapping with interference are damaged, with more severe overlap causing greater signal loss. This is consistent with the SINR and NMSE trends of MSTFT, WPCT, and FrFT. The anti-jamming performance of MSTFT, WPCT, and FrFT is generally worse because, in LEO satellite anti-jamming scenarios, high-power LEO satellite signals always severely affect and cause misjudgment in interference detection and suppression. The direct application of traditional time-frequency analysis-based interference suppression methods yields poor results. Their performance degrades rapidly with the increase in the input JSR because the overlap between the desired signals and interference signals in the TF or FrFT domain increases with the number or energy of interference signals, damaging desired signals overlapping with interference during suppression, with a more severe overlap causing a greater signal loss.