Practical detection using sparse signal separation

Due to the dynamic motion of the sea, radar detection of small maritime targets can be difficult. Airborne maritime surveillance platforms are also increasingly required to operate at higher altitudes where backscatter from the sea becomes stronger. The focus of this paper 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 work looks at the selection of the penalty parameter, which is 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.