## 3 Method Description
### CWI Resistance  
In the practical application of eLoran systems, CWI is a common and challenging issue, often originating from other radio equipment or intentional jamming activities. CWI potentially poses a direct threat to signal quality and demodulation accuracy.  
As previously discussed, the EPD algorithm relies on BPF that are ineffective against in-band noise and CWI. Although digital signal processing techniques can provide some suppression of in-band interference, a considerable amount of residual often persists. Additionally, the use of analog notch filtering, while aimed at mitigating interference, can also inadvertently damage the spectral integrity, resulting in signal distortion. In contrast, the PSSD algorithm utilizes advanced interference suppression techniques. As detailed in Section 3.1, it employs truncation windows to reduce interference energy and employs spectral smoothing filtering to further decrease the interference modulus power, significantly enhancing the system's resistance to CWI.  
To demonstrate the interference suppression advantages of the PSSD algorithm, two sets of experimental examples are provided (see Section 4.1 for CWI parameter settings):  
1. Noise-free scenario, \"\(-\)\" modulation, 2 CWIs are introduced to compare the impact of different processing methods on phase difference stability.  
Figure 7 illustrates that without truncation windows and phase smoothing, the method cannot effectively resist CWI even in a noise-free environment, leading to unstable phase differences and potential demodulation errors. In contrast, after the truncated window and smoothing with Gaussian weight coefficient, the amplitude spectrum and phase difference curve (yellow lines) are smoother, restraining interference and maintaining demodulation accuracy to some extent. Calculation reveals that the weighted phase differences from the red and yellow phase difference curves are \(-0.0973\pi\) and \(-0.1411\pi\) respectively. Accordingly, based on the threshold (\(-\pi/10\)), incorrect (\"0\") and correct (\"\(-\)\") demodulation results are obtained, respectively.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**SNR**} & \multicolumn{3}{c}{**ESNR (dB)**} & \multicolumn{3}{c}{**DAR (\%)**} \\ \cline{2-7}  & **Before** & **After** & **\multirow{2}{*}{**\(\Delta\)ESNR (dB)**} & **PSSD** & **PSSD** & \multirow{2}{*}{**EPD**} \\  & **Filtering** & **Filtering** & & **with WS** & **Without WS** & \\ \hline \(-20\) & \(-10.18\) & \(-1.17\) & 9.01 & 43.04 & 32.55 & 33.47 \\ \(-15\) & \(-5.12\) & 3.86 & 8.98 & 63.05 & 33.81 & 45.32 \\ \(-10\) & \(-0.11\) & 9.03 & 9.14 & 84.61 & 52.94 & 68.40 \\ \(-5\) & 4.82 & 13.92 & 9.10 & 9* SNR = \(-10\) dB white noise scenario with 2 CWIs (matching the settings from example a); the DARs are compared to evaluate the different processing methods. Figure 8 showcases the statistical results of multi-groups of experiments. When SNR = \(-10\) dB and CWI exist, the average DAR of PSSD algorithm stands at 74.91%, which is notably higher than 61.99% of the EPD algorithm. This further validates the new algorithm's ability to resist CWIs in a low SNR environment. The results depicted in Figure 8 provide solid evidence of the effectiveness and robustness of the PSSD algorithm in handling challenging interference conditions.  
This section is underpinned by experimental examples, which affirm the effectiveness of the PSSD algorithm in countering CWI. In both noise-free and low SNR scenarios, the algorithm's phase smoothing processing proficiently sustains phase difference stability and notably augments demodulation capabilities. When compared with the EPD algorithm, the PSSD algorithm exhibits outstanding superiority in anti-CWIs. In Section 4, more comprehensive performance analysis under diverse interference conditions will be presented to further illustrate the robustness of the PSSD algorithm.