Multiple Window Time-Varying Spectrum Estimation

Metin Bayram and Richard G. Baraniuk
Department of Electrical and Computer Engineering
Rice University
Houston, TX 77251-1892


We propose a new method for the time-varying spectrum estimation of non-stationary random processes. Our method extends Thomson's powerful multiple window spectrum estimation scheme to the time-frequency and time-scale planes. Unlike previous extensions of Thomsom's method, in this paper we identify and utilize optimally concentrated window and wavelet functions and develop a statistical test for extracting chirping line components. Examples on synthetic and real-world data illustrate the superior performance of the technique.