New method for time-varying harmonic frequency tracking

A tracking method is presented for tracking time-varying harmonic frequencies. The approach is taken in two steps: based on the observation (x(t)), a raw frequency estimate y(t) is first computed using an adaptive Pisarenko harmonic decomposition (PHD) method. In practice, results are quite noisy due to a short data record and frequency changes. The results are then fed into an event-detection tracking unit to extract the trajectory information about the underlying frequencies. The frequency estimates are fed back to the adaptive PHD algorithm to produce successive estimates of frequencies. The method uses an artificial intelligence planning strategy called least commitment, for which the idea is to hold off decision-making further in time.<
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