# Towards Automatic Recognition of Wakes Generated by Dark Vessels in Sentinel-1 Images
## 4 Discussion and Conclusions  
Different reference scenarios were analyzed to characterize the problem of recognition of wakes generated by dark vessels in SAR images to achieve an effective maritime surveillance. In this concern, it is clear that limitations in terms of SAR images availability, revisit time, and delivery time play an important role when the images are to be exploited for surveillance applications. However, the upcoming SAR satellite constellations based on inclined orbits with different right ascension of the ascending node will enable nighttime observations and very short revisit time, e.g., 1 h by the complete ICEYE constellation. This is expected to overcome the limitations of the current SAR satellites and constellations, which operate in dusk/dawn orbit and, practically, share the same line-of-nodes. In addition, with the NRT (near real-time) mode, the information on suspect vessels is made available to the user within 30 min from the acquisition, thus enabling reliable and operational detection of dark vessels. The first analyzed scenario focused on an area in which the wind field is homogeneous and ships with characteristics similar to GoFast ships in terms of velocity and length/beam ratio are identified. In Section 3, an example of such scenario is shown and discussed. The results show that thanks to homogeneity of the sea clutter, ship detection by wake recognition is very effective. No false detections are observed in the tested cases, even if the application to a wider dataset is required to confirm this evidence. The second scenario implies a case in which the sea is affected by natural surface film. In this case, the wake recognition also shows very good performance when the wake appearance is more distinguishable than the dark features over the sea surface. In details, the most visible wakes are identified with the highest level of confidence, that is  
Figure 8: (a)Additional trials for Scenario 3 (1800 \(\times\) 1800 pixels, 18 km \(\times\) 18 km). (b)recognized wakes, i.e., image pixels crossed by the maximum number of candidate wakes. the maximum number of reconstructed lines crossing a single image pixel. On the contrary, a lower level of confidence, i.e., less than the maximum number of reconstructed lines crossing a pixel, is estimated for the wakes whose visibility are similar to the dark features over the surface. It is evident that a trade-off is required between the probabilities of false and missed detection. In the present case, the method was set to decrease the former, thus also increasing the latter. The third scenario has been revealed as the most challenging for the proposed approach. In fact, it investigated the case in which both high and low wind speed areas are imaged. This situation is prone to generate both false and missed wake detections. The first ones have been clearly individuated in the processed dataset, and they are generated when the transition is so sharp and almost linear in shape. As far as missed wakes are concerned, even if they were not observed in the analyzed images, they can occur across the transition depending on the motion directions of the vessels. For each scenario, three trials have been analyzed, and the results show that:  
1. The best applicative scenario is the one characterized by homogeneous sea clutter, in which a 100% of success rate of wake identification is observed, with no missed wakes. 2. When the scenarios include prominent linear features (i.e., natural surface film almost linear or sharp linear transitions from bright to dark image portions), the detection rate is affected. In details, we have observed that in one out of three scenarios with natural surface film, the wake detection shows false alarms, because the dark features related to natural surface film is recognized as wake due to almost linear shape in the tile. Instead, the area with low wind speed is well managed by the proposed techniques, which does not provide any false detections related to brighter spots in the dark low speed areas.