## 4 Simulation Experiment and Discussion
### Experimental Results  
In this section, we will statistically analyze the experimental results. The \"BEST\", the \"WORST\", the \"MEAN\", the \"MEDIAN\", and the \"Standard Deviation (SD)\" for all the compared algorithms and scenarios are tabulated and discussed, as given in Tables 2-7. It should be noted that the global objective function constructed in this paper represents the joint detection probability of multi-UAVs. To carry out a more fine-grained analysis, the detection probability of each UAV in the same scenario is counted separately. 1. Scenario 1 The results for scenario 1 are tabulated in Table 2. The acquired results indicate the following conclusions: * For the first UAV, the proposed CC-MPSO obtained the best results in terms of the statistical parameters \"BEST\", \"MEAN\", and \"SD\". Meanwhile, RI-MAC has obtained the best results for the remaining statistical parameters. For the second UAV, CC-MPSO has achieved the best results for all the considered statistical parameters. * Except for the standard PSO, the other algorithms perform well in scenario 1. This suggests their capability to formulate effective search paths within uncomplicated settings. However, further examination is warranted to evaluate their efficacy in more intricate scenarios. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**UAV\({}^{*}\)**} & **Statistical Analysis** & \multirow{2}{*}{**CC-MPSO**} & \multirow{2}{*}{**PSO**} & \multirow{2}{*}{**MPSO**} & \multirow{2}{*}{**ECPO-ME**} & \multirow{2}{*}{**ACO**} & \multirow{2}{*}{**RI-MAC**} \\ \cline{5-5}  & **Analysis** & & & & & & & \\ \hline \multirow{5}{*}{UAV1} & BEST & **0.16603** & 0.14135 & 0.15926 & 0.15055 & 0.13548 & 0.16015 \\  & WORST & **0.15118** & 0.12125 & 0.12515 & 0.12835 & 0.10546 & 0.13456 \\  & MEAN & **0.15756** & 0.13456 & 0.13548 & 0.13456 & 0.11548 & 0.14568 \\  & MEDIAN & **0.15486** & 0.13875 & 0.13058 & 0.13816 & 0.12132 & 0.14125 \\  & SD & **0.00486** & 0.00587 & 0.01289 & 0.00898 & 0.00789 & 0.00985 \\ \hline \multirow{5}{*}{UAV2} & BEST & **0.18433** & 0.15165 & 0.14158 & 0.16489 & 0.14321 & 0.17189 \\  & WORST & 0.15984 & 0.12346 & 0.11356 & 0.12151 & 0.11285 & **0.16154** \\  & MEAN & **0.16865** & 0.13786 & 0.13156 & 0.14321 & 0.12486 & 0.13465 \\  & MEDIAN & **0.16423** & 0.14032 & 0.13486 & 0.14154 & 0.12154 & 0.13515 \\  & SD & **0.00358** & 0.00586 & 0.00786 & 0.00654 & 0.00145 & 0.00865 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Statistical analysis of the outcome of all algorithms for scenario 5. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**UAV\({}^{*}\)**} & **Statistical Analysis** & \multirow{2}{*}{**CC-MPSO**} & \multirow{2}{*}{**PSO**} & \multirow{2}{*}{**MPSO**} & \multirow{2}{*}{**ECPO-ME**} & \multirow{2}{*}{**ACO**} & \multirow{2}{*}{**RI-MAC**} \\ \cline{5-5}  & BEST & **0.16603** & 0.14135 & 0.15926 & 0.15055 & 0.13548 & 0.16015 \\  & WORST & **0.15118** & 0.12125 & 0.12515 & 0.12835 & 0.10546 & 0.13456 \\  & MEAN & **0.15756** & 0.13456 & 0.13548 & 0.13456 & 0.11548 & 0.14568 \\  & MEDIAN & **0.15486** & 0.13875 & 0.13058 & 0.13816 & 0.12132 & 0.14125 \\  & SD & **0.00486** & 0.00587 & 0.01289 & 0.00898 & 0.00789 & 0.00985 \\ \hline \multirow{5}{*}{UAV1} & BEST & **0.18433** & 0.15165 & 0.14158 & 0.16489 & 0.14321 & 0.17189 \\  & WORST & 0.15984 & 0.12346 & 0.11356 & 0.12151 & 0.11285 & **0.16154** \\  & MEAN & **0.16865** & 0.13786 & 0.13156 & 0.14321 & 0.12486 & 0.13465 \\  & MEDIAN & **0.16423** & 0.14032 & 0.13486 & 0.14154 & 0.12154 & 0.13515 \\  & SD & **0.00358** & 0.00586 & 0.00786 & 0.00654 & 0.00145 & 0.00865 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Statistical analysis of the outcome of all algorithms for scenario 3.