%B 53rd IEEE Conference on Decision and Control
%N February
%T Robust Parametric Estimation of Biased Sinusoidal Signals: a Parallel Pre-filtering Approach
%A Boli Chen
%A Gilberto Pin
%A Thomas Parisini
%V 2015-F
%D 2014
%P 1804-1809
%K Frequency estimation, 
Time-frequency analysis, 
Vectors, 
Noise, 
Lyapunov methods,  
Transient analysis
%J 2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC)
%L discovery10189793
%S IEEE Conference on Decision and Control
%I IEEE
%O This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
%C Los Angeles, CA, USA
%X In this paper, a parallel pre-filtering scheme is presented to address the problem of estimating the parameters of a sinusoidal signal from biased and noisy measurements. Extending some recent result on pre-filtering-based frequency estimators, a parallel pre-filtering scheme is proposed to deal with the unknown offset and bounded measurement perturbations, which are typically present in several practical applications. A simple frequency estimator, having parallel second-order pre-filters, is introduced. The behaviour of the proposed algorithm with respect to bounded additive disturbances is characterized by Input-to-State Stability arguments. Numerical examples shows the effectiveness of the proposed technique.