# GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation
## 6 Performance Evaluation with TEXBAT
### Scenario 2 of TEXBAT  
Detection results of SQM and RAIM in Scenario 2 are shown in Figure 9. Figure 9a shows the ratio metric, which is one of the most widely-used metrics in the SQM technique. It is defined as \((I_{E}+I_{L})/(2I_{P})\), where \(I_{E}\), \(I_{L}\) and \(I_{P}\) are the early, late and prompt taps on the in-phase component, respectively [15]. Here, the correlator spacing is set to 0.25 code chip; therefore, the ratio metrics should be about 0.75 when the spoofing signal is absent. It can be seen that the ratio metrics in Scenario 2 are constant throughout the experiment and fail to detect the spoofing attack. This is because the power of the spoofing signal is much higher, and no obvious disruptions occur in the drag-off process. Figure 9b shows the sum of the squares of the range residual error (SSE), which is a statistic in RAIM technology. It is employed to evaluate the consistency of the pseudorange measurements of different signals when more than four satellites are observed at the same time [16]. When the measurements are inconsistent, the range residual error will be large, and the SSE will be over a pre-assigned threshold, implying that the PVT results are unreliable [16]. Figure 9b shows that the SSEs are all beneath the threshold and fail to detect the spoofing attack. This is because that all of the tracking channels are taken over by the spoofing signals, and the code phases of these signals are manipulated sophisticatedly to generate consistent pseudorange measurements. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & \(\mathbf{M}\) & \(\mathbf{SDP_{1}}\) (\%) & \(\mathbf{SDP_{M}}\) (\%) & \(Imp\)(\%) & \(SVP\)(\%) \\ \hline ds2 & 7 & 79.7 & 97.3 & 17.6 & 82.5 \\ ds3 & 6 & 77.3 & 84.9 & 7.6 & 77.3 \\ ds4 & 8 & 64.9 & 78.7 & 13.8 & 61.2 \\ ds5 & 6 & 69.4 & 93.5 & 24.1 & 49.0 \\ ds6 & 6 & 46.4 & 81.8 & 35.4 & 71.5 \\ ds7 & 7 & 74.7 & 82.0 & 7.3 & 72.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Spoofing detection and validation performance in different spoofing scenarios of TEXBAT. Figure 10a shows the test statistics \(T(\mathbf{y})\) in Scenario 2. They are smaller than the threshold in the first 110 s when no spoofing signals are present. At about 110 s, spoofing signals are added, and the statistics are over the threshold because the code phases of the spoofing signals are not perfectly aligned with those of the authentic ones. The statistics increase when the code phase differences between authentic and spoofing signals are larger, indicating that the spoofing signals are more likely to be detected, which is consistent with the results in Figure 8. They stop increasing after the correlation peaks of the authentic and spoofing signals are completely separate (after about 210 s). Figure 10b shows the detection results of Scenario 2. Results larger than 0.5 mean that evil signals are detected. The red circles correspond to the results when seven signals and the blue points correspond to the results when only one signal is processed. Figure 10b shows that the detection performance is better when more signals are processed simultaneously. Figure 10: (**a**) Test statistics and threshold in Scenario 2; (**b**) Detection results in Scenario 2; results larger than 0.5 mean that there are evil signals. The red circles correspond to the results when seven signals are processed together, and the blue points correspond to the results when one signal is processed. Figure 9: (**a**) Ratio metric of signal quality monitoring (SQM) in Scenario 2; (**b**) SSE of RAIM in Scenario 2; the red dashed line denotes the threshold. Figure 11a shows \(r_{2}\) in Scenario 2. \(r_{1}\) is omitted since it is larger than four throughout the experiment. \(r_{2}\) is larger than four after 150 s, indicating that consistent signals are detected in the residual signal \(\mathbf{y}\). Thus, the evil signals can be judged as spoofing ones, and one of \(\hat{\rho}_{1}\) and \(\hat{\rho}_{2}\) corresponds to the authentic result.