Thales

Sextant Avionique

Thomson-csf Sextant

Pierre-Albert Breton

Stéphane Kemkemian

Richard Montigny

Vincent Corretja

Olivier Rols

G&eacute;rard Reynaud

Dominique Pastor

A method for determining wave height by means of a radar carried by an aircraft, the method implementing the following steps: a first step of pointing the antenna of the radar; a second step of determining the clutter acquisition plan according to the altitude of the aircraft; a third step of determining, for each clutter zone defined by the acquisition plan, two Doppler parameters PARA1 and PARA2 characterising the zone as a whole; a fourth step of calculating the average values of the parameters PARA1 and PARA2 over all of the zones in question; and a fifth step of estimating the wave height from the averages of the parameters PARA1 and PARA2. The wave height estimated in this way is transmitted to the aircraft and used to determine the conditions for the water landing of the aircraft.

Method for measuring wave height by means of an airborne radar

Upon each new detection, called pivot detection, by a radar system, the method includes the steps consisting of: grouping together, with the pivot detection, grouped detections, defined as detections that belong to a sweep preceding the sweep of the pivot detection and that have a non-nil probability according to a grouping criterion; filtering the grouped detections so as to keep only detections that are kinematically strictly coherent with the pivot detection, by: initializing a histogram, each dimension of which is a temporal variation of a coordinate measured by the radar system; computing a potential value interval for each coordinate of the pivot detection and each grouped detection; computing a minimum temporal variation and a maximum temporal variation for the or each coordinate from potential value intervals of the pivot detection and each grouped detection; incrementing the set of classes of the histogram whose index along each dimension is located between the computed minimum and maximum temporal variations; and detecting a target once at least one class of the histogram reaches a predefined value.

Method and system for detection by long integration of kinetically grouped recurring samples

The invention relates to devices for processing images making it possible to identify, to process and to select discrete light sources present in a video image composed of pixels. The aim is the presentation, in real time, to a user of a processed image allowing better recognition of light sources in a weakly contrasted image. In aeronautical use, this device affords a landing aid by allowing better recognition of runway lamps in conditions of degraded visibility, in particular in foggy weather. The invention relies on three major principles: 1) the main processing of images is performed only on a small number of pixels whose level is greater than a threshold; 2) a likelihood estimator evaluates the probability of existence of sources in the image; 3) the threshold is variable as a function of a certain number of parameters of the image.

Device for image processing with recognition and selection of light sources

The invention relates to a process and a system for voice recognition in a noisy signal. In a preferred embodiment, the system () comprises modules for detecting speech () and for formulating a noise model (), a module () for quantifying the energy level of the noise and for comparing with preestablished energy spans, a parameterization pathway () comprising an optional denoising module (), with Wiener filter, a module () for calculating the spectral energy in Bark windows, a module () for applying a configuration of shift values (), by adding these values to the Bark coefficients, as a function of the quantification (), so as to modify the parameterization, a module () for calculating vectors of parameters, and a block () for recognizing shapes, performing the voice recognition by comparison with vectors of parameters prerecorded during a learning phase.

Process for voice recognition in a noisy acoustic signal and system implementing this process

A method of voice recognition in a noise-ridden acoustic signal comprises a phase of digitizing temporal frames of the noise-ridden acoustic signal, a phase of parametrization of speech-containing temporal frames, a shape-recognition phase in which the parameters are assessed with respect to references pre-recorded in a reference space, a phase of reiterative searching for noise models in the noise-ridden signal frames, a phase of searching for a transition between the new noise model and the old model and, when the noise transition has been detected, a phase of updating the reference space, the parametrization phase including a step of matching the parameters to the new noise model.

Method and device for voice recognition in environments with fluctuating noise levels

The disclosed method uses the Wiener frequency filtering to suppress noise in noisy sound signals (u(t)). This method includes a preliminary step in which the sound signals (u(t)) to be noise-suppressed are digitized by sampling and subdivided into frames. The method then includes a first series of steps including the creation of a noise model on N frames, the estimating of the spectral density of the noise and of the energy of the noise model and the computing of a coefficient that reflects the statistical dispersion of the noise. It also includes a second series of steps including the computation of the spectral density of the signals to be noise-suppressed fore each frame. The coefficients of the Wiener filter are modified for each successively processed frame, by the parameters determined at the end of the two series of steps, so as to introduce an energy compensation and an adaptive overestimation of the noise.

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Pessac, France

Pierre-Albert Breton