A STAP clutter suppression algorithm based on sparse representation for small-array HFSWR. Issue 6 (3rd June 2022) - Li, Jiaming; Yang, Qiang; Zhang, Xin; Guo, Liang; Liang, Chao; Bai, Yang
ABSTRACT: In high-frequency surface wave radar (HFSWR) systems, the main-lobe of the receiving angle spectrum suffers from severe broadening due to a small-array aperture effect. This broadening causes more clutter components to be mixed into the main-lobe, resulting in target vessels more prone to be submerged in the clutter. This problem severely affects the target detection performance. A reduction in the number of array elements decreases the degrees of freedom (DOF), making clutter suppression more difficult. Space-time adaptive processing (STAP) has recently become a crucial tool for clutter suppression in advanced HFSWR systems, using two-dimensional data to increase DOF. Focusing on low DOF and typical nonhomogeneous clutter with high energy, this study proposes a STAP clutter suppression method by estimating clutter components accurately in the space-time domain based on sparse representation in few snapshots. The experimental results verify that the proposed algorithm provides high suppression performance for measured clutter.