Stationary Marine Target Detection With Time-Series SAR Imagery

Stationary marine targets, such as oil rigs and offshore wind turbines, usually show up like bright spots without or with trivial position shifts in multitemporal synthetic aperture radar (SAR) imagery. They will trigger considerable false alarms in target detection applications tasked with ship detection, if they are not identified. An algorithm for stationary marine target detection, developed based on the assumption that the apparent positions of a stationary target in multitemporal imagery are also stationary or nearly so, is proposed in this article. This algorithm requires a strict time-series of SAR images in temporal sequence as input. For each input SAR image, all targets on sea surface are initially detected with an iterative cell-averaging constant false-alarm rate detection algorithm, and their longitude and latitude positions are then used to identify whether they are stationary targets. Under this algorithm, a stationariness index with five levels ("unknown target," "suspected new stationary target," "stationary target," "suspected removed stationary target," and "removed target") is defined for each target and must be iteratively updated with the latest level of identification. The proposed algorithm is promising for monitoring the status of stationary marine targets over a large sea area, because the processing of all input SAR images follows the same procedure and meanwhile the stationariness index is generated and kept updated. Two examples with GF-3 and RADARSAT-2 images are presented to illustrate the effectiveness of the proposed algorithm in detecting both offshore wind turbines and oil rigs.