Detection in sea clutter using sparse signal separation

Radar detection of small maritime targets can be difficult due to the dynamic motion of the sea. Airborne maritime surveillance platforms are also increasingly required to operate in environments where the sea clutter is strong with persistent breaking waves resembling targets. The focus of this article is to investigate three sparse signal separation formulations using the short time Fourier transform as a dictionary. This approach has been demonstrated as effective in separating both stationary and moving targets from sea clutter but relies on the tuning of different parameters. The first part of this article looks at how to select these parameters which are essential to achieve good separation. Then, a number of practical detection schemes are presented that allow control of the false alarm rate. The algorithm performance is demonstrated using Monte Carlo simulation with synthetic targets injected into the Ingara medium grazing angle sea-clutter data set.