A gradient-adaptive lattice-based complex adaptive notch filter

Abstract

This paper presents a new complex adaptive notch filter to estimate and track the frequency of a complex sinusoidal signal. The gradient-adaptive lattice structure instead of the traditional gradient one is adopted to accelerate the convergence rate. It is proved that the proposed algorithm results in unbiased estimations by using the ordinary differential equation approach. The closed-form expressions for the steady-state mean square error and the upper bound of step size are also derived. Simulations are conducted to validate the theoretical analysis and demonstrate that the proposed method generates considerably better convergence rates and tracking properties than existing methods, particularly in low signal-to-noise ratio environments.

A novel fine Doppler frequency acquisition algorithm for BDS‐3 B1C signal based on an adaptive filter

“…The adaptive notch filter technique is widely used for singlefrequency sinusoidal signal enhancement and extraction, and single-frequency interference mitigation [26][27][28][29][30], because the adaptive notch filter is able to estimate the carrier frequency of the input signal accurately, which implies the adaptive notch filter can be used for the fine Doppler frequency estimation. Therefore, based on the adaptive notch filter, a low-complexity adaptive filter is proposed to conduct fine Doppler frequency acquisition.…”

“…where coefficients k 1 and k 2 are concerned with equivalent noise bandwidth B F of the 2-ord FLL, as Equation (30) shows.…”

Frequencies estimation of gearbox vibration signal based on normalized lattice filter with RLS-based algorithm

“…The adaptive algorithm used to update the internal parameters of the notch filter is another important element influencing the notch filter's frequency estimation performance. Gradient descent-based algorithms, such as the gradientlattice algorithm (GLA) [25] and the simplified gradientlattice algorithm (SLA) [26], are widely used, due to their ease of calculation. However, low convergence speed is an inherent problem with these algorithms.…”