ABSTRACT

The nonstationary clutter is one of the biggest challenge to ocean remote sensing radar system such as high frequency (HF) mixed-mode surface wave radar. The performance of space-time adaptive processing (STAP) degrades badly with limited homogeneous secondary training data support. Single dataset algorithms overcome the problem by working on primary data solely. But the heavy computational complexity as well as the inaccurate estimation of the clutter covariance matrix restricts the practical application of these methods. In this letter, we propose a novel reduce-rank-based single dataset STAP to suppress the nonhomogeneous clutter in practical HF radar system. A fast implementation of subspace tracking algorithm is introduced to estimate the clutter subspace as well as reduce the computational cost via pulse iteration method. The effectiveness of the proposed method is verified by both simulated and experimental data. The results show it outperforms traditional single dataset STAP methods and the nonstationary clutter can be greatly suppressed.

摘要

非平稳杂波是海洋遥感雷达系统（例如高频（HF）混合模式表面波雷达）面临的最大挑战之一。时空自适应处理（STAP）的性能会因有限的同类次要训练数据支持而严重下降。单一数据集算法通过仅处理原始数据解决了该问题。但是，繁琐的计算复杂度以及杂乱协方差矩阵的估计不准确，限制了这些方法的实际应用。在这封信中，我们提出了一种新颖的基于降秩的单数据集STAP，以抑制实际HF雷达系统中的非均匀杂波。引入了子空间跟踪算法的快速实现，以估计杂波子空间，并通过脉冲迭代方法降低了计算成本。仿真和实验数据均验证了该方法的有效性。结果表明，它优于传统的单数据集STAP方法，并且可以大大抑制非平稳杂波。