Abstract: The method according to the invention is a method for showing the localization error of a plurality of points of a georeferenced image, comprising the following steps: providing a georeferenced image, in which each image coordinate point is associated with announced values of the geographical coordinates defining the geographical localization of the object corresponding to that point of the georeferenced image; showing the georeferenced image. The method also comprises the following steps: providing, for each point of the plurality of points of the georeferenced image, an estimated value of the localization error specific to that point, said error not being uniform over the image; and showing the localization error for at least one point among the plurality of points of the georeferenced image so as to make it possible for a user to view the localization error.

Abstract: A method of modelling real objects represented in an image of the terrestrial surface, in particular buildings, on the basis of a geographically referenced image, the image being produced by an aerial or space sensor associated with a physical picture-capture model, comprises at least the following steps: choosing a parametric model of the external surface of the said real object; for several suites of parameters of the said model: projecting the parametrized model into the image by applying the physical picture-capture model, and evaluating the fit between the projected model and the radiometric characteristics of the image; and determining the parameters of the model for which the fit is the best so as to model the said object with these parameters. The method of modelling applies notably to teledetection, digital geography, to the construction of urban 3D databases or their updating.

Abstract: The invention relates to a method for determining a localization error (?) of a point (P0) of a raw image, comprising the following steps: estimating the value of a statistical magnitude (G) characteristic of a probability law (D(X, Y, Z)) of at least one terrain coordinate (X, Y, Z) associated with the point (P0) of the raw image, using a probability law (D(?1, . . . , ?n)) with magnitudes (?1, . . . , ?n) depending on the exposure conditions of the raw image and a localization function, deduced from an exposure function and a terrain model and applied for the image coordinate point (P0) of the raw image; and deducing the localization error (?) of the point (P0) of the raw image from the statistical magnitude (G).

Abstract: A navigation filter for a navigation system using terrain correlation delivering an estimation of the kinematic state of a carrier craft using a plurality of data includes the measurements returned by at least one terrain sensor, the model associated with the terrain sensor, the data from an onboard map, an error model for the onboard map, the measurements returned by an inertial guidance system, and a model of the inertial guidance system. The navigation filter also includes a first filter referred to as convergence filter, for example of the Kalman filter type, and a second filter referred to as tracking filter, for example of the particle filter type.

Abstract: A method for calculating a navigation phase for a carrier, in a navigation system involving terrain correlation, includes determining a navigability map in which each point of interest of an onboard map is associated with a navigability score. The method is applicable to all terrain aided navigation techniques, and allows the consideration of the quality of the onboard maps and terrain sensors used.

Abstract: A method of modelling real objects represented in an image of the terrestrial surface, in particular buildings, on the basis of a geographically referenced image, the image being produced by an aerial or space sensor associated with a physical picture-capture model, comprises at least the following steps: choosing a parametric model of the external surface of the said real object; for several suites of parameters of the said model: projecting the parametrized model into the image by applying the physical picture-capture model, and evaluating the fit between the projected model and the radiometric characteristics of the image; and determining the parameters of the model for which the fit is the best so as to model the said object with these parameters. The method of modelling applies notably to teledetection, digital geography, to the construction of urban 3D databases or their updating.

Abstract: A method of defining a navigation system comprising at least one inertial platform and involving terrain correlation, the estimations of the state vector of a platform being made by a navigation filter which furthermore accesses the data of an onboard map, allows the definition of the parameters relating to, respectively, the inertial platform and at least one terrain sensor allowing Terrain-Aided-Navigation, the definition of the parameters being carried out on the basis of computations carried out with the help of statistical syntheses not involving a modeling of the navigation filter.

Abstract: The method according to the invention is a method for showing the localization error of a plurality of points of a georeferenced image, comprising the following steps: providing a georeferenced image, in which each image coordinate point is associated with announced values of the geographical coordinates defining the geographical localization of the object corresponding to that point of the georeferenced image; showing the georeferenced image. The method also comprises the following steps: providing, for each point of the plurality of points of the georeferenced image, an estimated value of the localization error specific to that point, said error not being uniform over the image; and showing the localization error for at least one point among the plurality of points of the georeferenced image so as to make it possible for a user to view the localization error.

Abstract: A method for calculating a navigation phase for a carrier, in a navigation system involving terrain correlation, includes determining a navigability map in which each point of interest of an onboard map is associated with a navigability score. The method is applicable to all terrain aided navigation techniques, and allows the consideration of the quality of the onboard maps and terrain sensors used.

Abstract: A method of defining a navigation system comprising at least one inertial platform and involving terrain correlation, the estimations of the state vector of a platform being made by a navigation filter which furthermore accesses the data of an onboard map, allows the definition of the parameters relating to, respectively, the inertial platform and at least one terrain sensor allowing Terrain-Aided-Navigation, the definition of the parameters being carried out on the basis of computations carried out with the help of statistical syntheses not involving a modeling of the navigation filter.

Abstract: The invention relates to a method for determining a localization error (?) of a point (P0) of a raw image, comprising the following steps: estimating the value of a statistical magnitude (G) characteristic of a probability law (D(X, Y, Z)) of at least one terrain coordinate (X, Y, Z) associated with the point (P0) of the raw image, using a probability law (D(?1, . . . , ?n)) with magnitudes (?1, . . . , ?n) depending on the exposure conditions of the raw image and a localization function, deduced from an exposure function and a terrain model and applied for the image coordinate point (P0) of the raw image; and deducing the localization error (?) of the point (P0) of the raw image from the statistical magnitude (G).

Abstract: A navigation filter for a navigation system using terrain correlation delivering an estimation of the kinematic state of a carrier craft using a plurality of data includes the measurements returned by at least one terrain sensor, the model associated with the terrain sensor, the data from an onboard map, an error model for the onboard map, the measurements returned by an inertial guidance system, and a model of the inertial guidance system. The navigation filter also includes a first filter referred to as convergence filter, for example of the Kalman filter type, and a second filter referred to as tracking filter, for example of the particle filter type.