## 6 VCA Performance evaluation  
VCA performance has been evaluated with a set of simulations carried out at X band for the sensor summarized in Table 2. It deals with a standard single-pass interferometric configuration with an orthogonal baseline of \(B^{\perp}=30m\), height sensitivity of \(\Delta z=0.27\sigma_{\phi}\) (for a phase error expressed in degrees) and image resolution of 2.3 m in azimuth and 1.3 m in range [7]. By now, tests with real data have not been possible (despite they are mandatory for a proper validation of the technique) because no dataset with the required specifications 1 was available at the time this manuscript has been written. Future joint projects should consider new dedicated measurement campaigns where this and other methods can be tested and cross-correlated. The SPA, ICE and FER geometries have been processed in four different scenarios with the reference feature sets listed in Table 1. In scenario 0 neither sea surface nor ship motions are included whereas in scenario 1 only ship motions, in scenario 2 only sea surface and in scenario 3 both ship motions and sea surface. On the one hand, ship motions are mainly described by rolling and pitching with the first-derivative angular velocities fixed in Table 3. They are defined counter-clockwise with respect to the rotation axis. On the other hand, sea surface is modelled with the two-scale height profile for \(h_{l}\)=1.5 m, \(h_{s}\)=0.1 m, \(\lambda_{l}\)=100 m, \(\lambda_{s}=\lambda/(2\sin\phi)\)[33]. This last formula assures a Bragg scattering phenomena in the scene, which is sensitive to the operating wavelength [22]. Table 4 provides the similarity values calculated for each reference feature vector (\(S_{\Theta^{SPA}}\)\(S_{\Theta^{ICE}}\) \begin{table}
\begin{tabular}{|c|c|c|c||c|c|c|c|c|} \hline Scenario & Bearings & Motions & Sea surface & \(\beta\) & \(\dot{\delta}_{roll}\) & \(\dot{\delta}_{pitch}\) & \(\beta\) & \(\dot{\delta}_{roll}\) & \(\dot{\delta}_{pitch}\) \\ \hline
0 & [295:10:355]\({}^{o}\) & No & No & 295 & _-1.56_ & _-0.26_ & 335 & _-0.98_ & _-1.16_ \\ \hline
1 & [295:10:355]\({}^{o}\) & Right Side & No & 305 & _-1.43_ & _-0.52_ & 345 & _-0.76_ & _-1.32_ \\ \hline
2 & [295:10:355]\({}^{o}\) & No & 2 scale & 315 & _-1.32_ & _-0.76_ & 355 & _-0.52_ & _-1.43_ \\ \hline
3 & [295:10:355]\({}^{o}\) & Right Side & 2 scale & 325 & _-1.16_ & _-0.98_ & - & - & - \\ \hline \end{tabular}
\end{table} 
Table 3: Scenario configurations for simulations in Section 6.. Sea parameters are \(h_{l}\)=1.5 m, \(h_{s}\)=0.1 m, \(\lambda_{l}\)=100 m, \(\lambda_{s}=\lambda/(2\sin\phi)\). Rotational motions are expressed with first-order angular velocities in rad/s \begin{table}
\begin{tabular}{|c|c|c|c|c||c|c|c|c|c|} \hline \(\phi\) [\({}^{o}\)] & _20_ & \(r_{o}\) [\(Km\)] & _550_ & PRF [Hz] & _3630_ \\ \hline f [GHz] & _9.65_ & BW [MHz] & _135_ & \(\tau[\mu s]\) & _25_ \\ \hline \end{tabular}
\end{table} 
Table 2: The X-band SAR sensor based on DLR’s TerraSAR-X to test VCA performance. **Figure 8.** Magnitudes of the Pauli interferograms normalized to the overall maximum obtained for the FER model with \(\beta=295^{o}\) and \(\phi=20^{o}\) in scenario 1 (a) and 3 (b). Both images present a snapshot of the point of view with transparent surfaces. They have superimposed colored points that locate the azimuth x slant-range positions of the four PePS defining the feature set of FER ship, as stated in Table 1. Note how the presence of the sea distorts the ship signature making PePS isolation by simple eye inspection (colored arrows) more difficult. \(S_{\Theta^{FER}}\)) when the three ships are processed in the four scenarios. As observed, ships are well classified in almost all situations preserving a reasonable confidence even with clutter. Two items are important, namely: 1) non-uniform azimuth shifts help in some cases to improve classification and 2) sea clutter appears to be the most adverse factor.