Research Article
Wind Turbine Clutter Suppression for Weather Radar Using Improved Ridge Regression Approach
@INPROCEEDINGS{10.1007/978-3-030-51103-6_40, author={Yv Ji and Xu Yao and Xiaodong Wang and Mingwei Shen}, title={Wind Turbine Clutter Suppression for Weather Radar Using Improved Ridge Regression Approach}, proceedings={Multimedia Technology and Enhanced Learning. Second EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part II}, proceedings_a={ICMTEL PART 2}, year={2020}, month={7}, keywords={Weather radar Ridge regression Clutter suppression}, doi={10.1007/978-3-030-51103-6_40} }- Yv Ji
Xu Yao
Xiaodong Wang
Mingwei Shen
Year: 2020
Wind Turbine Clutter Suppression for Weather Radar Using Improved Ridge Regression Approach
ICMTEL PART 2
Springer
DOI: 10.1007/978-3-030-51103-6_40
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.
