Frequency Estimation of Sinusoidal Signals in Multiplicative and Additive Noise

In this paper, frequency estimation of sinusoidal signals in multiplicative and additive noise is addressed. Based on the parametric localization of distributed sources and the minimax theorem, an eigenanalysis-based frequency estimator is proposed. Furthermore, we present processing and analysis for pseudofrequency estimates in the proposed method. Especially, a priori knowledge of multiplicative noise is not required as compared with the distributed signal parameter estimator (DSPE). Monte Carlo experiments are carried out to evaluate performance. Simulation results confirm that the proposed method provides better performance than the nonlinear least squares (NLS) approach and the conventional MUSIC algorithm for separating closely spaced sinusoidal signals in multiplicative and additive noise.