An Adaptive Algorithm for Real-Time Multi-Tone Estimation and Frequency Tracking of Non-Stationary Signals

Real-time harmonic estimation and frequency tracking are well known pivotal problems in many engineering domains. Incidentally, similar challenges arise in tokamak plasma diagnostics' data processing where the spectral complexity of characteristic signals poses additional obstacles. Building up on previous Kalman filter based developments, this paper describes an adaptive real-time algorithm for simultaneous multi-component frequency tracking and harmonic estimation in noisy signals. Furthermore, the proposed gain adaptation method is shown to improve estimation performance in cases where the amplitude ratio of signal components differs by roughly up to three orders of magnitude. A series of selectively devised tests were carried out for challenging the performance and determining the operational limits of the algorithm when aiming to provide accurate estimates, in real-time, of both instantaneous amplitude and phase plus the instantaneous frequency evolution of dominant tones in noisy signals. Finally, results and performance issues are discussed.