## 3 Results  
To evaluate the performance of the suggested algorithm, 100 sensors were randomly deployed on an area 100 \(\times\) 100 m. The jammer moved randomly, starting at point 40, 30 before constantly accelerating. The transmission range of the sensors was 15 m. The jammer had a transmission range of 17 m. The transmission power was set to \(-36\) dBm and \(-35\) dBm for the nodes and jammer, respectively. The noise floor was about \(-95\) dBm and the SNR threshold value was 21.8, as presented in Figure 3.  
Figure 4 shows the jammer, and the nodes within the jammer's transmit range are isolated and affected by the jammer's signal. Figure 4: JRSS received by selected boundary nodes. Figure 3: Network deployment. The red star is the jammer, the yellow circles represent the jammed nodes, green circles are the boundary nodes, and the blue circle denotes the boundary nodes' neighbors. The red arrow is the JRSS received by the boundary node, and the dotted line is the bidirectional link between nodes. It is clear that the nodes located outside the jamming region are affected by JRSS. When the jammer is moving, the status of the node changes from unjammed to jammed, or a jammed node becomes an isolated node, as shown in Figure 5.  
This illustration represents boundary nodes affected during jammer movement. In (a), the node detects JRSS at t = 0 and becomes a jammed node in the period from t = 11 s to t = 23 s. In this period, we lost the jammer information. For the same reason, in b, c, and d, the boundary nodes are missing the tracking information while the jammer changes its position. The system stops tracking for the first time when encountering missing data, which t = 11 s shows in Figure 6. For this analysis, defining the boundary nodes while the jammer moving is mandatory. The unjammed nodes received the JRSS as noise, and the SNR decreased based on the amount of JRSS received by the node. Based on this observation, we defined a new threshold for boundary node selection. Figure 5: The jammer’s signal received by boundary nodes while the jammer is moving: **(a)** tracking information missing in the period from t = 10 s to t = 23 s; **(b)** tracking information missing in the period from t = 10 s to t = 33 s; **(c)** tracking information missing in the period from t = 10 s to t = 22 s and; and **(d)** tracking information missing in the period from t = 10 s to t = 56 s.  
Figure 6: EKF output. The system stops tracking at t = 11 s.  
We examined the BNST at time steps 10 s, 20 s, 30 s, and 50 s. Figure 7 represents the average SNR measured by each sensor. Figure 8 shows the BNST estimated with different jammer's transmission range 15 m, 20 m, 30 m and 35 m.  
As described in the previous section, all nodes estimate the average SNR and match it with the system threshold, or the SNR threshold and BNST value. If the computed value falls between two these values, the sensor turns itself into a boundary node and begins tracking the jammer until its average SNR drops below the SNR threshold or rises above the BNST value. In Figure 7a, there are ten nodes that became boundary nodes by themselves and starting to read the JRSS. At time step 17 in (b), four elected boundary nodes had an average SNR between the SNR threshold and the BNST. Figure 8: The BNST, the SNR threshold and the average SNR computed at each boundary nodes when the jammer’s transmission range is changed: (a) jammer’s transmission range = 15 m; (b) jammer’s transmission range = 20 m; (c) jammer’s transmission range = 30 m; and (d) jammer’s transmission range = 35 m.  
Figure 7: The average SNR computed at boundary nodes: (a) time steps = 10 s; (b) time steps = 20 s; (c) time steps = 30 s; and (d) time steps = 50 s.  
Figure 9 shows the jammer's estimated location and its real position, found by applying EKF to measure the JRSS by selected boundary nodes at every time step. In this study, we compared BNST with SDBR and BCP.