风电场雷达杂波动态重构抑制方法

随着风电场的大范围建设，风轮机杂波对雷达的干扰问题日益严重，常规杂波抑制方法难以有效解决风轮机杂波（WTC）干扰问题，因此提出了一种利用动态字典对风轮机杂波进行稀疏重构进而抑制的方法。首先，建立了WTC干扰下的雷达信号模型并分析了风轮机杂波的信号特征。其次，依据WTC的时频特征提出了一种微动参数粗估计方法，利用粗估计结果缩小了字典稀疏重构参数范围，在此基础上利用正交匹配追踪（OMP）算法对字典进行动态生成，并逐级更新字典原子。最后，通过动态字典对风轮机杂波信号进行稀疏重构，从而实现了对WTC的有效抑制。通过仿真实验，分析了风轮机杂波对目标检测的干扰影响，验证了基于动态稀疏重构的风电场杂波抑制方法在不同情况下的有效性。

Wind turbine clutter suppression method based on dynamic reconstruction

With the wide-scale construction of wind farms, the interference problem of the Wind Turbine Clutter (WTC) on radar detection is becoming more and more serious, but the conventional clutter suppression method is difficult to solve this problem. Therefore, this paper proposes a wind turbine clutter suppression method using dynamic dictionary to sparse reconstruction. Firstly, the radar signal model under the WTC is established and the signal characteristics of wind turbine clutter are analyzed. Secondly, a rough estimation method of micro-motion parameters is proposed based on the time-frequency characteristics of WTC. Based on the rough estimation results, the range of dictionary sparse reconstruction parameter is reduced. On this basis, the dictionary is dynamically generated by the Orthogonal Matching Pursuit (OMP) algorithm to update the basis step by step. Finally, the sparse reconstruction of the WTC is realized by the dynamic dictionary to achieve the purpose of suppressing the WTC. Through the simulation, the influence of wind turbine clutter on the target detection is analyzed, and the effectiveness of the WTC suppression method based on dynamic sparse reconstruction in different situations is proved.