Vricon Systems Aktiebolag

Saab Ab

Vricon Systems Ab

Maxar International Sweden Ab

Saab Vricon Systems Ab

Leif Haglund

Folke Isaksson

Johan Borg

Per Carlbom

Ingmar Andersson

Johan Bejeryd

Ola Nygren

Anton Nordmark

Zoran Sjanic

Sanna Ringqvist

Ingemar Andersson

Magnus Brege

Patrik Dammert

Jonas Dehlin

Tomas Toss

Thomas Beckman

Manne Anliot

Bard Frostad

Michael Felsberg

Anna Birgersson

Michael Olofsson

Bertil Grelsson

Gustav Tapper

Klara Hellgren

Fredrik Rosenqvist

Bård Frostad

Bejeryd Johan

The present invention relates to a method and an arrangement for providing a 3D model of an environment. The method comprises the step of forming a mesh modelling the environment in three dimensions, said mesh comprising nodes interconnected by edges and having surfaces boarded by the edges, wherein each node is associated to a 3D coordinate in a geographical coordinate system, determining for a plurality of the nodes and/or surfaces and/or edges in the mesh a mesh uncertainty and associating the determined mesh uncertainty to the corresponding node and/or surface and/or edge.

Method and arrangement for providing a 3D model

A method for resolution enhancement of images is described comprising the steps of providing () at least a first two dimensional (2D) test image, providing () a high-resolution 3D map, providing () a Machine Learning Network (MLN), extracting (), from the high-resolution 3D map, a 2D submap, comprising geocoded 2D coordinate data and texture information, extracting () a 2D subimage from the 2D test image, which 2D subimage is an image of the same area as the 2D submap, and training the MLN, using the high-resolution 2D submap and the 2D subimage.

Resolution enhancement of aerial images or satellite images

The present disclosure relates to a method and system for navigation of an aerial vehicle. The method () comprises providing () a sensor image from an aerial vehicle sensor and repeatedly, until at least one predetermined criterion is reached, performing the steps: setting () input data comprising information related to pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle; providing () at least one two-dimensional perspective view image based on the input data, where the at least one two-dimensional perspective view image is obtained from a database comprising three-dimensional geo-referenced information of the environment, said three-dimensional geo-referenced information comprising texture data; and comparing () the sensor image and the at least one two-dimensional perspective view image.

Method and system for navigation of a vehicle

The present disclosure relates to a position determining unit () for a land or sea based object and a method for determining a position. The position determining unit comprises or has access to a three dimensional map () comprising three dimensional geo-referenced position data. The position determining unit comprises further map part selector means () for selecting a part of the three dimensional map () so as to obtain a geo-referenced position associated to the selected part, at least one measurement instrument () arranged to obtain bearing and/or distance information related to the land or sea based object, and a computing and control unit () arranged to relate each obtained bearing and/or distance information to a corresponding obtained geo-referenced position and to determine a geographical position of the land or sea based object based on the bearing and/or distance information and the corresponding obtained geo-referenced positions.

Position determining unit and a method for determining a position of a land or sea based object

The present invention relates to a method and arrangement for developing a 3D model of an environment. The method comprises steps of providing a plurality of overlapping images of the environment, each image associated of navigation data, providing distance information, said LIDAR information comprising a distance value and navigation data from a plurality of distance measurements, and developing the 3D model based on the plurality of overlapping images and the distance information. The step of developing the 3D model comprises the steps of providing the 3D model based on the plurality of overlapping images; and updating the 3D model with the distance information using an iterative process.

Method and arrangement for developing a three dimensional model of an environment

The present invention relates to a system () and method for determining a relation between a first scene and a second scene. The method comprises the steps of generating at least one sensor image of a first scene with at least one sensor; accessing information related to at least one second scene, said second scene encompassing said first scene, and matching the sensor image with the second scene to map the sensor image onto the second scene. The step of accessing information related to the at least one second scene comprises accessing a 3D map comprising geocoded 3D coordinate data. The mapping involves associating geocoding information to a plurality of positions in the sensor image based on the coordinate data of the second scene.

Method and system for determining a relation between a first scene and a second scene

A method is provided, which comprises generating at least three images of an area of interest from at least one imaging system, the generated images being provided from at least three different angles, establishing point correspondence between the provided images. The method further involves generating at least two sets of three-dimensional information based on the provided images, wherein the at least two sets of three-dimensional information are generated based on at least two different combinations of at least two of the at least three provided images of the area of interest. The method further includes comparing the at least two sets of three-dimensional information so as to determine discrepancies, and providing information related to the imaging system or errors in the images based on the determined discrepancies.

Method and system for analyzing images from satellites

The present disclosure relates to a method () for rendering a simulated Synthetic Aperture Radar, SAR, image. The method comprises providing () a digital surface model or the like comprising 3D coordinate data in a geo-referenced coordinate system, determining () a sub-section of the digital surface model, and obtaining () the simulated SAR image based on the subsection of the digital surface model, wherein substantially each point in the simulated SAR image being associated to a 3D coordinate in the geo-referenced coordinate system.

Method and system for rendering a synthetic aperture radar image

A method for classifying a terrain type in an area is provided, which comprises the steps of obtaining a plurality of overlapping aerial images of the area, calculating at least one terrain type index for each part of each of the aerial images which lies in the area, where the at least one terrain type index represents the terrain type, determining at least one terrain type index for each part of the area based on the calculated at least one terrain type index for each part of each of the aerial images, and classifying the parts of the area for which at least one pre-determined conditions is met as containing the terrain type, wherein at least one of the at least one predetermined condition relates to a value of the determined at least one terrain type index. Also provided is a system and a computer program product.

Method and system for classifying a terrain type in an area

The present disclosure relates to a method () and system for determining the position of a target. The method comprises a step of measuring () with a range and direction measuring device the position of at least one reference object relative to the position of the range and direction measuring device. The method further comprises a step of marking () the at least one reference object in a geo-referenced three-dimensional map so as to obtain a geo-referenced position of the at least one reference object. The method further comprises a step of measuring () with the range and direction measuring device the position of the target relative to the position of the range and direction measuring device. The method further comprises a step of calculating () a position of the target based on the measured position of the at least one reference object relative to the position of the range and direction measuring device, based on the measured position of the target relative to the position of the range and direction measuring device, and based on the obtained geo-referenced position of the at least one reference object.

Target determining method and system

A method for estimating values for a set of parameters of an imaging system is presented. At least two pictures having an overlapping area are taken with the imaging system from different positions. Pulses are sent out to the area, the reflected pulses are detected and distances between a sender of the pulses and the respective point where the pulses were reflected are calculated based on the travel time of the pulses. First information about the area is calculated based on the pictures. Second information related to the calculated distances to the area is also calculated. Values for quantities contained in the first and second information are compared. If the value for a quantity obtained from the first information differs from the value obtained from the second information, values and/or an error estimate for the set of parameters of the imaging system is calculated based on the difference.

Method and an apparatus for estimating values for a set of parameters of an imaging system

The invention relates to a method for building a 3D model of an area of interest on the surface of a planet. The method comprises providing a plurality of 2D images from satellites, where each 2D image out of the plurality of 2D images at least partly covers the area of interest. Also, each subarea of the area of interest is covered by at least two images, taken from different angles, out of the plurality of 2D images. Bundle adjustments are performed for the plurality of 2D images and the area of interest is divided into parts. For each part of the area of interest at least one combination and preferably all possible combinations out of two images covering that part of the area of interest are taken. Said two images are taken from the at least two images, taken from at least two different angles, out of the plurality of 2D images. Further, for each part of the area, point matching correspondence is established for a set of points for each such combination of two images. The sets of points are combined if more than one set of points exists. Even further, for each part of the area, a 3D model of said part of the area of interest is built based on the combined set of points. The 3D models from each part of the area of interest are combined to a 3D model of the whole area of interest. The invention also relates to a system, a computer program and a computer program product.

Method and a system for building a three-dimensional model from satellite images

The invention relates to a method for identifying a difference between a first 3D model of an environment and a second 3D model of the environment. The first and second 3D model each comprise a plurality of points or parts, wherein each point or part of the first and second model comprises geometrical information and texture information. Corresponding points or parts of the first and second 3D model are matched based on the geometrical information and/or the texture information. The matched points or parts of the first and second model are compared to determine at least one difference value based on the geometrical information and the texture information of the first and second model. A difference between the first and second model is identified if the at least one difference value exceeds a predetermined value. The invention also relates to an arrangement, a computer program, and a computer program product.

Method and arrangement for identifying a difference between a first 3D model of an environment and a second 3D model of the environment

The invention relates to a method for navigation of an aerial vehicle. The method comprises providing a sensor image from an aerial vehicle sensor. The method also comprises to repeatedly, until at least one predetermined criterion is reached, perform the step of setting input data, where the input data comprises information related to pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle, the step of providing a two-dimensional image from a database based on the input data, where the database comprises three-dimensional geo-referenced information of the environment, and the step of comparing the sensor image and the two dimensional image from the database. The method further comprises using the input data for which the two images correspond best to each other for determining at least one of the following quantities pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle.

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Brokind, Sweden

Leif Haglund