Wind Farms Clutters Micro-motion Features Analysis And Detection For Weather Radar

As a special kind of large obstacles,Wind farms can produce serious interference to weather radar detection equipment.Wind farms are different from general static obstacles,the echoes from wind farms have strong scattering and Doppler spectral broadening characteristics,so they cannot be filtered out completely using the traditional ground clutter filtering technology.Therefore,the research on the micro-motion features analysis and detection technology of wind farms clutter for weather radar can provide corresponding theoretical basis and technical support for the wind farms clutter suppression techniques,and it has great significance on improving the reliability of weather radar targets detection.Firstly,the technology of time-frequency analysis and singular value decomposition(SVD)are used respectively to analyze the micro-Doppler features of wind farms echoes,which is based on the signal model of the wind farms echoes obtained by the scattering points superposition theory,and the validity of the simulation results is also verified by contrasting and analyzing with theoretical derivation.Secondly,the corresponding characteristic parameters are constructed based on micro-Doppler characteristics of wind farms clutter,and the micro-motion features of wind farms echoes are extracted based on SVD technology.In addition,the micro-motion features of wind farms clutter are compared and analyzed with those of weather targets when weather targets exist.Meanwhile,according to the difference of wind farms clutter from weather targets echoes,the features of wind farms clutter based on Level-II data are also extracted by constructing a set of characteristic parameters based on Level-II data.Finally,wind farms clutter is detected and identified based on the fuzzy logic theory by analyzing the statistical properties of characteristic parameters constructed based on Level-II data.In addition,the detection method of wind farms clutter is verified by combining several sets of typical Level-II data,and the experimental results show that the method can realize the detection of wind farms clutter both under ordinary weather conditions and special weather conditions.