Wind turbine clutter mitigation using morphological component analysis with group sparsity  

作　　者：WAN Xiaoyu SHEN Mingwei WU Di ZHU Daiyin 

机构地区：[1]College of Computer and Information,Hohai University,Nanjing 211100,China [2]Key Laboratory of Radar Imaging and Microwave Photonics&Ministry of Education,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China

出　　处：《Journal of Systems Engineering and Electronics》2023年第3期714-722,共9页系统工程与电子技术（英文版）

摘　　要：To address the problem that dynamic wind turbine clutter(WTC)significantly degrades the performance of weather radar,a WTC mitigation algorithm using morphological component analysis(MCA)with group sparsity is studied in this paper.The ground clutter is suppressed firstly to reduce the morphological compositions of radar echo.After that,the MCA algorithm is applied and the window used in the short-time Fourier transform(STFT)is optimized to lessen the spectrum leakage of WTC.Finally,the group sparsity structure of WTC in the STFT domain can be utilized to decrease the degrees of freedom in the solution,thus contributing to better estimation performance of weather signals.The effectiveness and feasibility of the proposed method are demonstrated by numerical simulations.

关 键 词：weather radar wind turbine clutter(WTC) morphological component analysis(MCA) short-time Fourier transform(STFT) group sparsity 

分 类 号：TM315[电气工程—电机] TN959.4[电子电信—信号与信息处理]