Wind farms clutters have the characteristics of strong scattering and the Doppler spectrum spreading due to the blades rotation, the radar echoes can not be filtered out easily using the traditional ground clutter filter, hence causing the false detection and identification of meteorological targets in the process of target detection, which is an important influence factor on the new generation weather radar echoes. Based on the analysis of wind farms echoes’ characteristics distinguished from those of meteorological target echoes, some suitable feature parameters are chosen, and a robust good adaptive fuzzy logic system of wind farms clutters detection and identification is developed by using the secondary products (Level II) data and the Fuzzy Inference System (FIS), in which the membership functions of each feature parameters and the corresponding logical rules are defined by constructing probability distribution histogram and the one dimensional range distribution of the corresponding feature parameters. Several groups of typical Level II data are collected to test and verify the proposed method, the experimental results demonstrate the reliability of the proposed algorithm.%风电场杂波具有强散射性和由于其叶片旋转导致的频谱展宽特性，其雷达回波很难用传统的杂波滤波器滤除，进而导致气象目标探测过程中的误检测与误识别，这是影响新一代气象雷达探测性能的一个重要因素。该文通过分析风电场杂波区别于气象目标的回波特性，基于气象雷达二次产品(Level-II)实测数据选取某些特征参量，通过构造特征量的概率分布直方图和1维值域分布确定用于识别风电场杂波的各个特征量的隶属度函数，并设置相应的逻辑规则，利用模糊逻辑推理系统(FIS)实现风电场杂波的自适应检测与识别。通过采集几组典型的 Level-II 数据对所提方法进行测试与验证，均较为准确地识别出存在于气象雷达视野内的风电场杂波，实验结果证明了该文算法的可靠性。
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