Differentiating Noisy Radiocommunications Signals: Wavelet Estimation of a Derivative in the Presence of Heteroscedastic Noise
Paul David Baxter, GRAHAM J. G. UPTON · Journal of the Royal Statistical Society Series C (Applied Statistics) · 2005
Summary Radio scientists require estimates of the rate of change in rain-induced signals. Unfortunately, these signals are observed in the presence of atmospheric noise, which has a variance that is dependent on temperature, pressure and other climatic variables. We develop a systematic approach to the problem, using wavelet differentiation combined with coefficient-dependent thresholding, and illustrate the considerable benefits that this provides over more conventional techniques.