Single dataset method for spread-Doppler clutter suppression in HF hybrid sky-surface wave radar
In high-frequency hybrid sky-surface wave radars, the spread-Doppler clutter (SDC) compromise low-velocity target detection performance. Generally, adaptive filter methods achieve clutter suppression by estimating a clutter-plus-noise covariance matrix from target-free training data, which are typically obtained from neighbouring range bins. Under certain circumstances, the clutter statistics change significantly across adjacent bins. To deal with this problem, a single dataset algorithm is proposed to suppress the SDC without secondary data. Firstly, a spatial orthogonal projection matrix is introduced to block the target component in the cell under test. Afterwards, a localised processing method is derived, using previously constructed clutter samples, to suppress the SDC. According to the experimental results, the proposed method can achieve better clutter suppression performance based on real data.
