Automatic optimization of adaptive notch filter's frequency tracking

Estimation of instantaneous frequency of narrowband complex sinusoids is often performed using lightweight algorithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently introduced adaptive notch filtering algorithm. Analysis shows that, under Gaussian random-walk type assumptions, the resulting solution converges in mean to the optimal frequency estimator. A simplified one degree of freedom version of the filter, recommended for practical applications, is also proposed. Finally, a comparison of performance with six other state of the art schemes is performed. It confirms the improved tracking accuracy of the proposed scheme.