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Research Article

A WTC suppression algorithm for weather radar based on weighted schatten p-norm minimization

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Pages 70-79 | Received 27 Jul 2022, Accepted 13 Dec 2022, Published online: 28 Dec 2022
 

ABSTRACT

The Matrix Completion (MC) method can effectively suppress the wind turbine clutter (WTC) of the weather radar, however its recovery accuracy suffers from the low signal-to-noise ratio (SNR) of the real measured weather signal. Moreover, the singular value distribution of the observation matrix constructed by the measured radar data has no sharp cut-off characteristic, which results the rank can not be well approximated and also reduces the recovery accuracy. In this paper, a non-convex MC algorithm based on weighted Schatten p-norm is proposed for the WTC suppression in Doppler frequency domain. Experiments are carried out on the measured signal data, and the results demonstrate that compared with the commonly used nuclear norm minimization (NNM) model, the weighted Schatten p-norm minimization (WSNM) model can further improve the recovery accuracy of weather signal and realizes the superior estimation performance of spectral moment.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

All the data generated or analysed in this study are available from the corresponding authors on reasonable request.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [No. 61771182, No.62271190], Natural Science Foundation of Jiangsu Province of China [BK20221499], and Science and Technology on Electronic Information Control Laboratory.

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