Comparaison d'estimateurs de fréquence à complexité algorithmique réduite

De nombreux algorithmes, basés sur une modélisation Auto Régressive du signal, ont été proposés pour des problèmes d'estimation de fréquence de signaux périodiques. Nous nous intéressons ici aux performances statistiques de tels estimateurs, et proposons des formules approchées du biais et de la variance des estimées. Les résultats obtenus permettent de mettre en évidence l'influence de la fréquence recherchée, du rapport signal sur bruit et du nombre de points sur les performances de l'estimateur

Particle detection and velocity measurement in laser Doppler velocimetry using Kalman filters

International audienceThe paper discusses a processing technique for LDV data, based on the use of two Kalman filters, enabling the presence of particles to be detected and their velocity to be inferred. This method turns out to be suitable for the design of real-time integrated velocimeters. A first estimator, based on the use of a Kalman filter, deals with the amplitude of the Doppler signal. A second one, using an extended Kalman filter, allows particle velocity estimation, which is assumed to be a constant. Finally, the estimator is studied by means of Monte Carlo trials obtained from synthesized signals, and its performance is then compared to the Cramer-Rao bound

Autocorrelation Fitting for Texture Orientation Estimation

International audienceThe problem of short-term texture orientation is dealt with in this paper through autocorrelation fitting. Actually, the computation of the estimated autocorrelation sequence from a textured oriented image brings about the apparition of an oriented pattern. This pattern is looked upon, in this work, as a Gaussian curve, the parameters of which give an estimated orientation. Those parameters are estimated by a two-dimensional (2-D) curve fitting on a particular region of the autocorrelation. The determination of this region is done automatically thanks to watersheds. The algorithm is developed for synthetic textured images but appears to be effective when applied to real life oriented images

Real-Time Parametric Estimation of Velocity Using Optical Feedback Interferometry

International audienceA low-cost laser sensor using optical feedback interferometry has been designed to measure velocities. With digital signal processing based on an order two autoregressive model of the optical power, an inaccuracy of about 0.5% can be reache

Red blood cell velocity estimation in microvessels using the spatiotemporal autocorrelation

International audienceThis paper deals with the problem of red blood cell velocity measurement in microvessels using dynamic video microscopy. More precisely, the problem of one-dimensional red blood cell velocity estimation is addressed, using algorithms based on the spacetime image obtained when a single line from the video, taken inside and along the vessel axis, is mapped into an image as a function of time. Flowing red blood cells generate an oriented and textured spatiotemporal plane, the orientation of which is related to their velocity. In order to perform space- and time-localized velocity estimations, orientation estimations have to be done locally in the spatiotemporal plane. Therefore, we propose the use of the autocorrelation sequence, the orientation of which is also related to the velocity. The region of interest of the autocorrelation, containing the velocity information, is selected using a watershed algorithm. We finally suggest two different algorithms estimating the spatiotemporal plane orientation upon the aforementioned region. Results and comparisons of these methods are proposed, using a controlled experiment and real-life blood flow video sequences

Two-Dimensional Frequency Estimation with Multiplicative Noise Using Non-Causal Minimum Variance Representation

International audienceIn this paper, the problem of two-dimensional (2D) frequency estimation of a complex sinusoid embedded in a white Gaussian additive noise and a multiplicative noise is addressed. For this purpose, we derive a noncausal minimum variance representation, the coefficients of which are described according to the frequencies to be estimated. Therefore, estimates are given without a complete computation of the power spectral density over the 2D frequency plane, but directly from the coefficients. Accuracy and robustness of this new 2D frequency estimator are statistically assessed by Monte Carlo simulations. The results obtained show that a good local frequency estimation can be directly achieved with the proposed model, even for signal embedded in multiplicative noise

Two-Dimensional Frequency Estimation Using Autocorrelation Phase Fitting

International audienceThe problem of two-dimensional (2D) frequency estimation of a complex sinusoid embedded in a additive white Gaussian noise is addressed. A new frequency estimator based on a least squares plane fitting of the estimated autocorrelation phase of the signal is derived. This algorithm requires a 2D phase unwrapping step which can be easily done. This algorithm is shown to be unbiased and attains the Cramer Rao bounds for high signal-to-noise ratio (SNR > 0 dB). Accuracy and robustness of this new 2D frequency estimator are statistically assessed by Monte Carlo simulations. The results obtained show that a good local frequency estimation can be achieved with a very simple algorithm, and a very small number of points are used for the autocorrelation estimation

Velocity Measurement Using Phase Fitting of Analytic Spatiotemporal Images

International audienceIn this paper, the problem of one-dimensional (1-D) velocity estimation is addressed, using two-dimensional (2-D) spatiotemporal orientation estimation. A new frequency estimator based on a least square plane fitting of the estimated autocorrelation phase has been previously developed and is applied here to random textured images for the problem of velocity estimation. This algorithm requires the computation of the analytic autocorrelation and of a 2-D phase unwrapping step. Then, a plane fitting applied to the unwrapped phase gives an estimation of the spatiotemporal image orientation. Finally, we show in this work that the velocity can be estimated successfully in the spatiotemporal plane with the use of a 2-D frequency estimator

Mesures Sans Contact de Vitesse Réelles Par Vélocimètre Laser Temps-Réel, Faible Coût

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