论文部分内容阅读
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。
The clutter of wind farms has strong scatter and spectral broadening due to the rotation of the blades. The radar echoes are hard to be filtered by traditional clutter filters, which leads to false detection and misrecognition in the process of meteorological target detection Is an important factor affecting the detection performance of the new generation of weather radar. In this paper, by analyzing the echo characteristics of clutter in wind farms different from those of meteorological targets, some characteristic parameters are selected based on the measured data of Level-Ⅱ, and the histograms of probability distributions and 1-D values The domain distribution is used to identify the membership function of each feature of clutter in wind farms, and the corresponding logic rules are set. The fuzzy logic inference system (FIS) is used to realize the adaptive detection and identification of clutter in wind farms. By collecting several sets of typical Level-II data, the proposed method is tested and validated, and the clutter of wind farms in the field of vision radar is more accurately identified. Experimental results show the reliability of the proposed method.