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.

摘要

在高频表面波雷达（HFSWR）系统中，接收角谱的主瓣由于小阵列孔径效应而遭受严重的展宽。这种加宽导致更多的杂波成分混合到主瓣中，导致目标船只更容易淹没在杂波中。这个问题严重影响了目标检测性能。阵列元素数量的减少会降低自由度 (DOF)，从而使杂波抑制更加困难。时空自适应处理 (STAP) 最近已成为高级 HFSWR 系统中杂波抑制的关键工具，它使用二维数据来增加自由度。专注于低自由度和典型的高能量非均匀杂波，本研究提出了一种STAP杂波抑制方法，基于少量快照中的稀疏表示，在时空域中准确估计杂波分量。实验结果验证了所提算法对实测杂波具有较高的抑制性能。