Estimation of Phase Noise Transfer Function

Nonparametric function estimation under Fourier-oscillating noise

In the popular deconvolution problem, the goal is to estimate a curve f from data that only allow direct estimation of another curve g, the convolution of f and a so-called error density. Unlike the standard assumption in deconvolution, we consider a more general setting where the characteristic function of the error density can have zeros. This problem is important as the characteristic functi...

Transfer function estimation for spaceborne telescopes

The on-orbit calibration of the transfer function (TF) of a spaceborne optical telescope is of paramount importance for the restoration of its recorded images. We propose a novel method based on a physical modeling of the TF and on the automatic extraction from the image of sub-images containing appropriate patterns such as step functions. A least-square criterion is computed with all the extra...

Thresholding in High Order Transfer Function Estimation

A problem in prediction error system identiication methods is estimation of pole locations. Typically, iterative numerical optimization methods are used. Reliable initial values are then necessary for good results. The parameterization is often done in the coeecients of transfer function polynomials or some canonical form. In this contribution we discuss a couple of issues related to the above ...

Transfer Function Identification from Phase Response Data

Wavelet Denoising of the Noise Estimation on Phase Matching

Most of the wavelet threshold denoising methods need to calculate the corresponding threshold. The estimation of noise variance will directly affect the effect of threshold denoising method. This paper describes a new phase matching method of the noise variance estimation. The real-time noise can be estimated by this method. The experiments show that the method can greatly improve the signal to...