Model-based spectral estimation of Doppler signals using parallel genetic algorithms

Conventional spectral analysis methods use a fast Fourier transform (FFT) o n consecutive or overlapping windowed data segments. For Doppler ultrasound signals, this approach suffers from an inadequate frequency resolution due to the time segment duration and the non-stationarity characteristics of t he signals. Parametric or model-based estimators can give significant impro vements in the time-frequency resolution at the expense of a higher computa tional complexity. This work describes an approach which implements in real -time a parametric spectral estimator method using genetic algorithms (GAs) in order to find the optimum set of parameters for the adaptive filter tha t minimises the error function. The aim is to reduce the computational comp lexity of the conventional algorithm by using the simplicity associated to GAs and exploiting its parallel characteristics. This will allow the implem entation of higher order filters, increasing the spectrum resolution, and o pening a greater scope for using more complex methods. (C) 2000 Elsevier Sc ience B.V. All rights reserved.