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The Doppler resolution for wind turbine clutter (WTC) returns usually gets degraded when using the operational standard scanning mode of meteorological radars. Here, the use of super-resolution techniques for improving the Doppler resolution is proposed. This study concentrates on the spectral estimation based on auto-regressive coefficients and the multiple signal classification algorithm. The former usually brings to light the four components of WTC, that is, the tower and the three blades, hence outperforming the classical Fourier spectral estimation. The latter, on the contrary, may be improper for scenarios with weather returns. To derive the pertinent conclusions, both classical spectral estimation and the commented super-resolution approaches are applied to simulated and real data coming from both WTC and weather.