# Dual Cancelled Channel STAP for Target Detection and DOA Estimation in Passive Radar
## 5 Experimental Results
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Full-Array STAP**} & \multicolumn{6}{c}{**AB-STAP**} \\ \hline  & **Delphin** & **T1** & **T2** & **T3** & **T4** & **Delphin** & **T1** & **T2** & **T3** & **T4** \\ \hline \(K=24\) & \(-7.5\) & \(-11.6\) & \(-6.7\) & \(-10.5\) & \(-4.8\) & \(-9.6\) & \(-9.3\) & \(-7.0\) & \(-7.8\) & \(-5.1\) \\ \(K=16\) & \(-3.1\) & \(-6.6\) & \(-2.2\) & \(-4.6\) & \(-3.3\) & \(-9.3\) & \(-8.6\) & \(-8.0\) & \(-6.5\) & \(-6.6\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Minimum nominal PFA for target detection (\(\log_{10}(\mathrm{PFA})\) ). From the results in Figure 11 and Table 3, the following considerations are in order:  
* Comparing Figure 11a,b, the full array STAP yielded a higher number of false alarms compared to the AB-STAP for a given PFA. The false alarms were mostly associated with persistent clutter structures, especially in those areas where the clutter power showed abrupt variations and the filter adaptivity was more likely to fail. * It is worth mentioning that the presence in the observed scene of other non-cooperative moving targets during the acquisition cannot be excluded. * When the training data were reduced to \(K=16\) (Figure 11c,d), the more localised adaptation capability allowed the AB-STAP scheme to better handle the clutter discrete and reduce the number of false alarms without compromising target detection. Conversely, in the full array STAP scheme, this was paid in terms of higher adaptivity loss, which raised the detection threshold to prevent a general increase of the false alarms, thus compromising the detection capability. * Looking at Table 3, when enough training data were available, both the detection schemes yielded remarkable results, allowing for target detection until low values of PFA. In the case of limited sample support, instead, the detection performance of full array STAP drastically decreased, while the AB-STAP approach was able to mostly preserve or even improve its outcomes (see for example T2 and T4). As a result, AB-STAP largely outperformed the full array STAP for all targets in this case. * By selecting a PFA of \(10^{-4}\), with \(K=24\) training data, all the considered targets would be detected by both the detection schemes. For \(K=16\), the AB-STAP would still detect all the targets, while the full array scheme would miss the detection of three out of five targets. After target detection, a proper estimation of target DOA was worthwhile for target localisation purposes. In fact, the array nominal BW was in the order of \(23^{\circ}\) (at broadside), thus providing poor target localisation capability. This was achieved by resorting to the space-time ML DOA estimation strategies formerly presented. In the full array STAP case, target angular position was estimated by finding the maximum of (2) over a bank of filters equally spaced by \(\delta\phi=0.1^{\circ}\) within the nominal BW, corresponding to a step smaller than BW/100. In the AB-STAP case instead, the closed form expression in (8) was exploited. For the purpose of our analysis, we neglected the angular ambiguity resulting from the antenna spacing larger than \(\lambda/2\), and we used the known target position in the estimation process to identify the non-ambiguous angular sector. Please note that this strategy did not affect our results, as we were mostly interested in small estimation errors around the true target DOA. The results of DOA estimation for each target are reported in Table 4 for an amount of training data equal to \(K=24\) and \(K=16\). The error with respect to the true target DOA values in Table 2 is reported in brackets. reduced. On the other hand, the AB-STAP approach was able to mostly preserve its good localisation performance, while requiring a lower computational complexity. Finally, Figure 12 shows the DOA estimation results obtained for the cooperative aerial target Delphin over consecutive scans.