An ocean clutter suppression method for OTHR by combining optimal filter and dictionary learning

In this paper, we consider the ocean clutter suppression problem for High-frequency (HF) sky-wave over-the-horizon radar (OTHR). A novel algorithm named Sparse Dictionary Represented Optimal Filter (SDROF) is proposed for target detection from strong clutter. The dictionary learning technique is used to capture the characteristics of ocean echo and to provide a better clutter estimate, while the well-known optimal filter ensures a statistically maximum output SCNR. SDROF can make use of the information of clutter in current range cell and approximate heterogeneous clutter environment more accurately. Thus, the proposed method performs better in the clutter background of OTHR, which is demonstrated by experimental data.