Direct frequency estimation based kalman adaptive IIR notch filter: State-space approach

A direct estimation based adaptive HR notch filter (DANF) based on state-space structure and discrete Kalman filtering is represented in this paper. It is well known that the state-space description not only provides a more detail explanation of the system characteristic compared to the input-output description but also has robustness to finite word-length effects. In addition, by using the discrete Kalman filtering, the fluctuation of an estimated parameter of the filter is reduced. In this paper, sinusoidal signal detection is employed to evaluate the performance of the proposed filter compared to the state-space structure of the DANF (SDANF). The computer simulation results confirm that the performance of the proposed filter has been improved over the SDANF.