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Wind turbine clutter mitigation using morphological component analysis with group sparsity
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作者 WAN Xiaoyu SHEN Mingwei +1 位作者 WU Di ZHU Daiyin 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2023年第3期714-722,共9页
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... 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. 展开更多
关键词 weather radar wind turbine clutter(WTC) morphological component analysis(MCA) short-time Fourier transform(STFT) group sparsity
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