# Joint Radar-Communication Optimization of Distributed Airborne Radar for AOA Localization
## 4 Numerical Results
### The Second Set of Parameters  
The simulation parameters of the experimental group are shown in Table 2. In terms of parameter selection, the literature selected for this subsection was [42]. The parameters not given in Table 2 were consistent with Table 1. The setting method for one experimental group and four control groups was consistent with Section 4.1, with a default communication range of 1.5 km. The corresponding numerical simulation results are shown in Figure 5.  
Figure 4: MSE versus time slot under the first set of parameters. (**a**) MSE when the time slot range was taken as 0–100. (**b**) MSE when the time slot range was taken as 10–20. (**c**) MSE when the time slot range was taken as 100. (**d**) The initial and final locations of UAVs. (**e**) The relationship between the time consumption per time slot of the JRCO algorithm and the number of UAVs.  
Figure 5a shows the MSE curves generated by each group when the time slot range was 0-100. Obviously, at this time, the curves corresponding to the experimental group, control group 3, and control group 4 decreased rapidly. Figure 5b shows a comparison of the curves between the experimental group and the control group 4 when the time slot was 10-20. It can be seen that in the early stages of algorithm iteration, the experimental group showed a better performance than any control group. Figure 5c shows the final results of MSE generated by each group for the 100 th time slot. At this time, the MSE of the experimental group (25.92 m) decreased by approximately 39.48% (16.91 m) compared to the MSE of control group 4 (42.83 m). The above numerical simulation results fully  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Symbol** & **Value or Range** \\ \hline Electromagnetic domain power & \(E_{\text{max}}\) & 2000 W \\ Maximum step size per time slot & \(\left[{}_{\text{max}}\right.\) & 300 m \\ The-coordinate range of the feasible area & \(\left[{}_{\text{min}},{}_{\text{max}}\right]\) & \(\left[{}_{0},10\right]\) km \\ The-coordinate range of the feasible area & \(\left[{}_{\text{min}},{}_{\text{max}}\right]\) & \(\left[{}_{0},2\right]\) km \\ The height of the feasible area & \(\left[{}_{\text{1}}LAV\right]\) & 500 m \\ Target location & \(\left[{}_{\text{x}_{\mu}},{}_{\text{y}_{\mu}},{}_{\text{z}_{\mu}}\right]\) & \(\left[{}_{\text{5}},10,1\right]\) km \\ The side length of departure area & \(b\) & 500 m \\ Collection of communication coverage & \(\rho\) & \(\left[{}_{\text{1}}.3,1.4,1.5,1.6,1.7\right]^{T}\) km \\ Variance of UAV location error & \(\sigma_{T}^{2}\) & 0.005 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The second set of parameters for numerical simulation.  
Figure 5: MSE versus time slot under the second set of parameters. (**a**) MSE when the time slot range was taken as 0–100. (**b**) MSE when the time slot range was taken as 10–20. (**c**) MSE when the time slot range was taken as 100. (**d**) The initial and final locations of UAVs.  
demonstrate the effectiveness of the proposed JRCO algorithm, and the joint optimization algorithm was suitable for a wide range of scenarios. Figure 5d shows the initial and final locations of the UAV swarm.