Ship detection and tracking is significant to the safe navigation, harbor surveillance and naval defence. In practice, the
ship cannot be properly detected and tracked due to the influence of the ambient or its moving attitude on its echo in
some images of the sequence. To solve this problem, we proposed a method for ship detection and tracking with time
sequential shipborne radar imagery. The method consists of the Kalman filter and the correlation matching technique.
The Kalman filter is used to predict the search areas of the ship in the next frame. The correlation matching technique is
applied to extract the position of the ship, which can automatically adjust the parameters of the Kalman filter. If the
tracked ship is incapable of detection in current frame, to keep the ship tracking successively, the predicted position
obtained by applying the Kalman filter can be used as the current position of the ship. It has been tested with 46
temporally consecutive X-band shipborne radar images to demonstrate the validity of the method. The result shows that
the ship in the shipborne radar images can be properly detected and tracked.
One of the main problems in ship detection is the presence of sea clutter inherent to radar imagery. A moving ship
detection method with time sequential shipborne radar imagery has been developed based on the radar backscattering
properties of ships. The method consists of the coherence image computation, ship detection threshold estimation and
false alarm removal. It has been tested with the X-band shipborne radar imagery. The results show that the method works