Adaptive denoising of electrostatic detecting signals based on wavelet transform

The forms of the electrostatic detecting signal and the interfering signal are analyzed to extract and identify the electrostatic signals of targets correctly. The wavelet shrinkage method for denoising based on Stein's unbiased risk estimate (SURE) is provided for signal processing in electrostatic detecting. The principle and modified scheme of denoising method based on SURE are explained. The means of adaptive adjustment of learning rate is introduced, and then the unbiased risk estimate of signal can be obtained with high operating speed. This method can be verified with the simulative program by using Matlab, and the denoising results are proper. In comparison with other wavelet shrinkage methods, it is concluded that the means adopted in this paper is suitable to process the electrostatic detecting signal which has complicated frequency components.