Adaptive instantaneous frequency estimation of multi-component FM signals

Abstract

Estimation of the instantaneous frequency (IF) of multicomponent FM signals with additive Gaussian noise is considered. A reduced interference distribution (RID) with high resolution is used for time-frequency representation of signals. If the IF law is a nonlinear function of time, the bias and variance of the estimate depend on the window length. The optimal window length for bias-variance tradeoff depends on the unknown IF law, hence calling for an adaptive algorithm with time-varying and data-driven window length to resolve this tradeoff. The adaptive estimation of multiple IF laws is based on tracking the component maxima in the time-frequency plane. Simulation results for multi-component signals are comparable with those obtained for mono-component signals when the components are well separated.