## 5 Simulation and Analysis
### Distributed Jammers of Same Topology in Different Scenarios  
The topology of a set of distributed jammers is obtained using a distributed inference algorithm. Simulations verify the feasibility and effectiveness of the proposed distributed interference optimisation strategy in this topology. Figure 7 shows the interference scenarios and the corresponding set of game strategies for the distributed interference sources at moments t1 and t2 in the same topology. At the moment t1, the BERs of the LEO signals received by the jamming target receiver are \(5.53\times 10^{-2},8.71\times 10^{-2},3.42\times 10^{-2}\), from left to right. At the moment t2, four LEO satellite signals need to be jammed. The BERs of the LEO star signals received by the receiver are \(3.87\times 10^{-2}\), \(4.72\times 10^{-2}\), \(5.32\times 10^{-2}\), \(6.42\times 10^{-2}\), from left to right. Low-orbit satellite signals are received with a BER on the order of \(10^{-2}\). From the BER point of view, it can be seen that the model has good interference effectiveness and the receivers in this region are not able to successfully decode the valid data. Figure 8 represents the regional interference coverage for the two scenarios. When the jamming signal does not achieve full area coverage, the distributed jamming source increases the power of the appropriate jamming signal to achieve a full-range area strike. The jamming system demonstrates a strong jamming coverage capability. It is not only able to achieve the basic one-layer coverage with enhanced two-layer coverage effect but also has the potential to accomplish three-layer or even multiple-layer coverage. This multi-layered interference greatly enhances the strength and effectiveness of the interference, causing greater obstruction to the normal decoding and information extraction at the receiver. Figure 6: Distributed interference simulation model. In the scenario at the moment t1, the main interference source game solves for the Nash equilibrium point, corresponding to utility function values of 3.2872, 3.1349, and 2.9372, from left to right. In the scenario at the moment t2, the utility function values corresponding to the Nash equilibrium points are solved by each main interference source through the game, from left to right, as 3.2317, 3.5121, 3.6391, and 3.4317. As can be seen in Figure 9, this topology is able to converge in terms of time-averaged coverage of the interference region after using the proposed optimisation method. The one-fold coverage converges to 100%; the two-fold coverage converges to 50.3588%; and the three-fold and above coverage finally converges to 20.7062%. This result shows that the interfering signal can effectively achieve full coverage in the whole domain range and can use less optimisation time to complete the stable coverage effect, which improves the interfering efficiency. Figure 8: The regional interference coverage for the two scenarios. (**a**) The regional coverage of the landing field by the distributed jamming source at the moment t1, when the game has not converged and (**b**) the regional coverage of the landing field at the moment t2, when the distributed jamming source game converges. Figure 7: Set of distributed interference source strategies in different scenarios. (**a**) Set of distributed interference source strategies at moment t1. (**b**) Set of distributed interference source strategies at moment t2. Figure 10 represents the variation curve of the BER of the jamming target receiver during the process of the jammers going from off to on to off. When the jammers are not turned on, the BER is on the order of \(10^{-6}\), indicating that the system is able to achieve normal communication and positioning. When the jammers are turned on, the BER is stably distributed between \(3\times 10^{-2}\) and \(7\times 10^{-2}\). Effective jamming is achieved, and the quality of the communication link decreases significantly.