Spatio-temporal combined ground-penetrating radar clutter suppression based on empirical mode decomposition and Karhunen-Loeve transform
Due to factors such as environment,the signals received by ground-penetrating radar(GPR)contain various clutter interfer-ence,posing high challenges in subsurface anomaly interpretation and late-stage imaging.Clutter,primarily including noise,antenna-cou-pled waves,and surface direct waves,cannot be eliminated effectively using single data processing methods.Hence,this study proposed a spatiotemporal combined clutter suppression method.In the temporal dimension,threshold processing based on empirical mode de-composition(EMD)was applied to the data of all survey points in the echo profile,achieving effective noise removal.In the spatial di-mension,the Karhunen-Loeve(KL)transform was employed to remove residual interference in the entire radar echo profile by utilizing the correlation of target echoes and the randomness of clutter at all survey points.Both theoretical simulation and measured data process-ing verify that the method proposed in this study is effective in eliminating clutter and highlighting weak signals.
万方数据
维普
