A moving ship produces a set of waves in a characteristic linear “V” pattern. This pattern, or some of its components, can often be detected in ocean imagery produced by satellite-borne Synthetic Aperture Radar (SAR) sensors operating at L-band. Some wake components, notably the turbulent wake, may extend for 5–15 km behind the ship. As ship wake detection can provide information such as ship direction and speed, the detection of these wakes can play an important role in satellite surveillance of shipping. Described is research done on the use of the Radon transform to automatically detect ship wakes in Seasat ocean imagery. The objective of the research was twofold: to automatically detect ship wakes and to differentiate ship wakes from other linear ocean features produced by the underwater topography and existing sea conditions. An ADA (Automatic Detection Algorithm) based on the Radon transform was developed and applied to the Seasat imagery. The basic system performs the Radon transform of the SAR image, then detects bright and dark peaks produced in the transform by wakes (or other linear features) in the image. As the Radon transform essentially integrates the image intensity along every straight line through an image, each integral becomes one element in transform space. This integration process averages out the intensity fluctuations due to noise, thereby increasing the signal-to-noise ratio of the feature of interest in the transform space relative to that in the original image. A number of additional processing techniques were developed and tested to improve the PD (probability of detection) and reduce the PFA (probability of false alarm). To date, the use of an ADA, which combines a high-pass filter followed by a normalized Radon transform and a Wiener filter, has been shown to reliably distinguish wake peaks from false alarms. © 1990 IEEE
