Review of ship detection from airborne platforms

Remote-sensing techniques for application to ship detection are assessed. The most commonly-used sensor is a search radar and secondly a side-looking airborne radar (SLAR). Radars can detect ships tinder a variety of conditions. The most common method of ship detection is to use search radars for location and then visible, low-altitude passes for identification or verification. Detection is performed manually in most cases. Use of the visible spectrum is largely restricted to the use of video and photographic cameras for documentation and identification. Specialized systems have been developed which use laser or strobe lights for scene illumination. Infrared sensors have also been used to detect ships. SLAR or side-looking airborne radar is frequently used for ship detection. Ship detection algorithms are not used because of positional uncertainty in the imagery, SLAR-equipped aircraft use radar to manually detect the ship and then use visual means to identify the vessel or to determine compliance to legislation related to discharge or fishing. Synthetic aperture radar (SAR) has been studied extensively. Interpretation of SAR imagery can provide ship position, heading and speed. Under certain conditions, relative size and type of vessel have been determined. SAR interpretation algorithms have been extensively developed for satellite SAR systems, and are applicable to airborne systems. Detection of ships using SAR is achieved by detecting the ship reflection, which is typically very intense, as well as by detecting the ship's wake. The ship's wake is composed of a v-shaped feature and an area of less sea clutter extending zip to 15 km behind the ship. These features are largely dependent on wind speed. The minimum size vessel detected under different wind conditions has been estimated for a typical airborne system based on similar estimations for satellite systems. Work on using a combination of sensors, visible, IR and SAR has been reported. The data are subjected to image recognition analysis to confirm detection and to classify the type of target.