## 4 Results and Discussion
### DoA Estimation Results  
To verify DoA estimation performance of the two-row ESPAR antenna using the generalized PPCC-MCP algorithm, which uses all 90 available calibration planes, \(N=18\) available antenna radiation patterns were divided into 3 separate groups having different angle tilt in elevation, as shown in Tables 1 and 2. In result, \(n_{up}=\{1,\,2,\,3,\,4,\,5,6\}\), \(n_{down}=\{7,8,9,10,11,12\}\), and \(n_{mid}=\{13,14,15,16,17,18\}\) were created as sets of steering vectors numbers associated with the specific two-row ESPAR antenna radiation patterns that can be created when particular steering vectors sets, namely \(V^{n_{up}}=\left\{V^{1},\,V^{2},\,V^{3},\,V^{4},\,V^{5},V^{6}\right\}\), \(V^{n_{down}}=\left\{V^{7},\,V^{8},\,V^{9},\,V^{10},\,V^{11},V^{12}\right\}\), and \(V^{n_{mid}}=\left\{V^{13},\,V^{14},\,V^{15},\,V^{16},\,V^{17},V^{18}\right\}\), are used. It allows verification of DoA estimation performance when \(g_{\delta,LL}\) is calculated using each of steering vectors set separately but also when they are combined in order to find the most appropriate combination for the two-row ESPAR antenna. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \(n\) & \(V^{n}\) & **Steering Vector Short Name** & \(\varphi_{max}\) & \(\theta_{max}\) \\ \hline
1 & \([001101\,010100]\) & \(V^{30}_{UP}\) & \(30^{\circ}\) & \(46^{\circ}\) \\ \hline
2 & \([100110\,0010]\) & \(V^{90}_{UP}\) & \(90^{\circ}\) & \(46^{\circ}\) \\ \hline
3 & \([010011\,00010]\) & \(V^{150}_{UP}\) & \(150^{\circ}\) & \(46^{\circ}\) \\ \hline
4 & \([101001\,100010]\) & \(V^{210}_{To test DoA estimation accuracy in a detailed way, 360 test horizontal directions \(\varphi_{t}\in\{0^{\circ},\,1^{\circ},\,\ldots,359^{\circ}\}\) for 90 elevation angles \(\theta_{t}\in\{90^{\circ},\,89^{\circ},\,\ldots,1^{\circ}\}\) were created and then corresponding RMSE and precision values were calculated for all 7 possible combinations of steering vector sets which are gathered in Table 3, at SNR = 10 dB and the obtained results are presented in Figures 11 and 12. As it can easily be observed in Figure 11, when a single set of steering vectors is used precision values deteriorate for low \(\theta\) values and the best results can be produced for \(\{V^{n_{mid}}\}\). For steering vector combinations involving at least 12 steering vectors, shown in Figures 11 and 12, one can acquire precision lower than \(19^{\circ}\) for all possible \(\theta\) angles, i.e., \(0^{\circ}<\theta\leq 90^{\circ}\). Surprisingly, the most accurate results with precision lower than \(11^{\circ}\) for all \(\theta\) angles can be obtained for the steering vector set \(\{V^{n_{mid}},V^{n_{down}}\}\) containing 12 vectors. When the complete set \(\{V^{n_{up}},V^{n_{mid}},V^{n_{down}}\}\) containing all 18 available steering vectors is used, the performance of generalized PPCC-MCP algorithm drops for \(\theta\in(9^{\circ},33^{\circ})\). \begin{table}
\begin{tabular}{c c c c} \hline \hline \(n\) & \(V^{n}\) & **Steering Vector Short Name** & \(\varphi_{max}\) & \(\theta_{max}\) \\ \hline
13 & \([000100\ 001000]\) & \(V^{30}_{MID}\) & \(30^{\circ}\) & \(52^{\circ}\) \\ \hline
14 & \([000010\ 000100]\) & \(V^{90}_{MID}\) & \(90^{\circ}\) & \(52^{\circ}\) \\ \hline
15 & \([000001\ 000010]\) & \(V^{150}_{MID}\) & \(150^{\circ}\) & \(52^{\circ}\) \\ \hline
16 & \([100000\ 00001]\) & \(V^{210}_{MID}\) & \(210^{\circ}\) & \(52^{\circ}\) \\ \hline
17 & \([010000\ 100000]\) & \(V^{270}_{MID}\) & \(270^{\circ}\) & \(52^{\circ}\) \\ \hline
18 & \([001000\ 010000]\) & \(V^{330}_{MID}\) & \(330^{\circ}\) & \(52^{\circ}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._  
\begin{table}
\begin{tabular}{c c c} \hline \hline \begin{tabular}{c} **Combination of Steering** \\ **Vector Sets** \\ \end{tabular}  & \ \begin{tabular}{c} **Steering Vectors** \\ **Numbers** \\ \end{tabular}  & \begin{tabular}{c} **Total Number of** \\ **Steering Vectors** \\ \end{tabular}