## 4 Results
This strategy effectively avoids misclassification and the unintended removal of signal bands, maintaining higher signal fidelity even under high JSR conditions. The simulation results show that at a JSR of 50 dB, the proposed method achieves FID improvements of 13.8% and 9.1% over WPT and KLT, respectively. Figure 9 presents the performance comparison of different interference suppression methods under the chirp jamming scenario. The simulation results show that the proposed method consistently maintains excellent suppression performance, with only a slight degradation as JSR increases. Compared with the TDPF algorithm, the proposed method achieves an average SINR improvement of approximately 8 dB, highlighting the performance limitations of TDPF when dealing with frequency-varying chirp interference. Additionally, the KLT algorithm outperforms the proposed method by about 0.5 dB in regards to average SINR. However, it is noteworthy that KLT suffers a significant fidelity drop of approximately 17.1% at a JSR of 50 dB. This indicates that, despite KLT's strong suppression capability, its fixed threshold mechanism may result in the unintended deletion of useful signal components. Overall, compared with other algorithms, the proposed method achieves a better balance between interference suppression and signal fidelity under chirp interference, effectively maintaining signal integrity while ensuring robust suppression performance. Under 10 us pulse interference conditions, 100 Monte Carlo simulations were conducted with a duty cycle of 20%, varying JSR between 30 and 60 dB, and the average SINR after suppression by each algorithm was calculated. The results in Figure 10 show that the average SINR of the method proposed in this paper is 3.0 dB higher than that of WPT, 19.8 dB higher than that of AFF, and 5.3 dB higher than that of FDPB. Figure 11 presents the performance comparison of the proposed algorithm under pulse jamming with different duty cycles (20%, 50%, and 80%). The simulation results indicate that increasing the duty cycle intensifies the impact of pulse jamming on the positioning signals. However, the proposed algorithm consistently demonstrates stable and effective suppression performance across all duty cycle conditions. Further analysis reveals that the influence of the duty cycle on algorithm performance is closely related to the JSR level. Under low JSR conditions,  
Figure 8: Performance comparison of different interference suppression algorithms under narrow-band interference. variations in duty cycle exert a more pronounced effect on the suppression performance of the TDPB algorithm, resulting in noticeable differences in SINR. As JSR increases and the interference energy becomes dominant, the performance gap caused by duty cycle variations gradually narrows. Figure 10: Performance comparison of different interference suppression algorithms under pulse interference. Figure 9: Performance comparison of different interference suppression algorithms under chirp interference. Under chirp interference, the signal capture performance is typically evaluated based on the peak clarity in the cross ambiguity function (CAF). The clearer the peak in the CAF, the stronger the capture algorithm's ability to locate the true Doppler frequency and pseudocode phase. Figure 11 compares the changes in the CAF before and after interference suppression processing, with the simulation conditions set as shown in Table 4.  
As shown in Figure 12a, before interference suppression processing, the high-power interference components remaining in the received signal severely disrupted the peak structure in the CAF, making it difficult to distinguish the peaks corresponding to the true signal. This situation is likely to cause misjudgments by the capture module, resulting in incorrect Doppler frequency and pseudocode phase estimates.