Abstract: The invention relates to a method for testing an air traffic management electronic system. The method includes receiving by the system of input data representative of a state of air traffic and establishing by the system of information related to air traffic as a function of the input data and delivery of the information to an electronic test device of the system. The method further includes determining by the electronic test device, as a function of the delivered information, of air traffic control instructions and providing said system with the instructions and receiving and processing of the instructions by the system.

Abstract: The invention relates to an air traffic management electronic system, including the steps of: reception by said system of input data representative of the state of air traffic; establishment by said system of information relative to the air traffic as a function of said input data and delivery of said information to an electronic test device of the system; determination by said electronic test device, as a function of the delivered information, of air traffic control instructions and providing said system with said instructions; reception and processing of said instructions by said system; according, to which said electronic device includes an algorithmic model for automatically determining instructions as a function of information relative to the air traffic, said model having been obtained during a learning phase, carried out by computer, of a deep learning neural network, as a function of a set of instructions previously provided by at least one air traffic controller to the system and information rela

Abstract: The present invention pertains to methods for managing resources in radar time, that is to say methods making it possible to manage in an optimal manner the scheduling of the boresightings performed. The method according to the invention firstly consists in supplying a table containing candidate boresightings. These candidate boresightings are those corresponding to the boresighting requests to be taken into account by the radar. Each boresighting is associated with a set of candidate frequencies, chosen from among the set of authorized frequencies, each set being defined specifically for each candidate boresighting. The candidate frequencies are determined so as to guarantee a diversity of the frequencies which are emitted by the radar, all boresightings taken together. The management of the boresighting requests takes into account in a dynamic manner the variations in the rotation speed of the antenna.

Abstract: The present invention relates to a method for detecting and grading the state and the evolution of wake turbulence caused by an aircraft, on the basis of the radar signals reflected by this turbulence, these signals being analyzed through analysis cells of given dimension in terms of distance and bearing. This method mainly comprises: a first preliminary detection step proper for detecting and locating turbulence in a cell, a second step for determining the strength of the detected turbulence, a third step for determining the age of the detected turbulence as well as the geometric parameters which characterize it. The method according to the invention advantageously makes it possible to detect wake turbulence and to determine at one and the same time the position and the strength of the latter as well as its stage of evolution. The invention applies in particular to the field of air traffic control and air safety in general.

Abstract: A high resolution Doppler analysis of a radiofrequency signal is exemplified by the analysis of air mass movement using meteorological radar. A high resolution spectral analysis method for a remotely sampled periodic radiofrequency signal, based on the application of a trellis autoregressive filtering Burg algorithm, is used to determine the natural frequencies of the received signal for each distance cell based on the determination of an optimum set of reflection coefficients of the signal. Reflection coefficients are the object of a regularization operation aiming to limit the numerical instabilities of the calculations. These regularized reflection coefficients are used to estimate the effective order of the identification model of the trellis filter, and to determine the natural frequencies of the signal by determining the arguments of the complex roots of the polynomial representing the transfer function of the trellis filter.

Abstract: The invention relates to the general field of high resolution doppler analysis of a radiofrequency signal. It deals more particularly with the analysis of the movement of air masses by means of a meteorological radar. The subject of the invention is a high resolution spectral analysis method for a remotely sampled periodic radiofrequency signal, based on the application of a trellis autoregressive filtering Burg algorithm, which can be used to determine the natural frequencies of the received signal for each distance cell based on the determination of an optimum set of reflection coefficients N of the signal. According to the invention, the reflection coefficients are the object of a regularization operation aiming mainly to limit the numerical instabilities of the calculations.

Abstract: A process for the separation of static and dynamic components of a sequence of images separated in time and taken under the same conditions. The process includes recording a first intensity of a first pixel in at least one area in the sequence of images, recording subsequent intensities for identical pixels to the first pixel in subsequent recorded images, and using pixel intensity sort criteria on intensity changes between the first intensity and the subsequent intensities to discriminate in the subsequent recorded images pixels showing minimal intensity changes from pixels showing larger intensity changes as the sequence process. The process includes forming from the pixels showing minimal intensity changes a part of the static component of the sequence of images.

Abstract: The process according to the invention used for weather radar images is used for dynamic monitoring of cloud masses, particularly to predict future changes. It consists essentially of creating the skeleton of each cloud mass, for several images at different times, determining the displacement vectors for segments of vectorized skeletons, and extrapolation to rebuild the predicted skeletons.

Abstract: The present invention pertains to the analysis of the frequency spectrum of a signal by a high-resolution method that is more precise than the Fourier transform when all that is available is a small number of samples of the signal. It pertains more particularly to a method for the autoregressive modelling frequency spectral analysis of a signal, known as Burg's maximum entropy method, and consists of a regularization of this method by means of a criterion similar to that already known to have been used in order to regularize the method of autoregressive spectral analysis known as the least error squares method, while at the same time keeping the advantages of Burg's maximum entropy method which are that it can be used in real time with a lattice type computation structure, that it can be extended to multisegment configurations and that it is robust with respect to computation noise, errors of quantization and rounding-off operations.