Abstract:
The detection of ships at sea is a difficult task
made more so by uncooperative ships, especially when using
transponder based ship detection systems. Synthetic Aperture
Radar imagery provides a means of observation independent
of the ships cooperation and over the years a vast amount of
research has gone into the detection of ships using this imagery.
One of the most common methods used for ship detection
in Synthetic Aperture Radar imagery is the Cell-Averaging
Constant False Alarm Rate prescreening method. It uses a scalar
threshold value to determine how bright a pixel needs to be in
order to be classified as a ship and thus inversely how many
false alarms are permitted. This paper presents by a method of
converting the scalar threshold into a threshold manifold. The
manifold is adjusted using a Simulated Annealing algorithm to
optimally fit to information provided by the ship distribution
map which is generated from transponder data. By carefully
selecting the input solution and threshold boundaries, much of
the computational inefficiencies usually associated with Simulated
Annealing can be avoided. The proposed method was tested on
six ASAR images against five other methods and had a reported
detection accuracy of 85:2% with a corresponding false alarm
rate of 1:01 10-7 .
