Open AccessSingle dataset method for spread‐Doppler clutter suppression in HF hybrid sky‐surface wave radar
Author(s) -
Tong Peng,
Wei Yinsheng,
Xu Rongqing
Publication year - 2017
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2016.3541
Subject(s) - clutter , doppler effect , computer science , radar , covariance matrix , constant false alarm rate , doppler radar , stationary target indication , noise (video) , filter (signal processing) , continuous wave radar , algorithm , radar horizon , artificial intelligence , remote sensing , radar imaging , computer vision , physics , telecommunications , geology , astronomy , image (mathematics)
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.