Abstract
The problem of clutter suppression is gaining importance because of many disadvantages. However, conventional clutter suppression methods cannot eliminate the great disturbances to radar system caused by wind turbines. An improved ridge regression algorithm is investigated to accurately estimate the spectral moment of the weather signal contaminated by wind turbine clutter (WTC) in this paper. Firstly, a weighted regression model is introduced to solve the problem that the strong collinearity of the data in the regression model leads to unstable parameter estimation. Then the optimal regression parameter in the model is obtained by generalized cross validation (GCV) to improve the estimation accuracy of weather signal. Theoretical analysis and simulation results show that the spectral moment recovered by the proposed algorithm has better accuracy and stability in lower SNR.
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Acknowledgement
This work was supported in part by National Natural Science Foundation of China (No. 41830110, No. 61771182).
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Ji, Y., Yao, X., Wang, X., Shen, M. (2020). Wind Turbine Clutter Suppression for Weather Radar Using Improved Ridge Regression Approach. In: Zhang, YD., Wang, SH., Liu, S. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-030-51103-6_40
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DOI: https://doi.org/10.1007/978-3-030-51103-6_40
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