Abstract: The present disclosure relates to a method (100) for rendering a simulated Synthetic Aperture Radar, SAR, image. The method comprises providing (110) a digital surface model or the like comprising 3D coordinate data in a geo-referenced coordinate system, determining (120) a sub-section of the digital surface model, and obtaining (130) 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.

Abstract: 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.

Abstract: 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.

Abstract: Various embodiments relate to a method (700) and system for geo-referencing at least one sensor image. The method comprises the steps of: generating at least one sensor image of a first scene with at least one sensor, accessing a 3D model of the environment comprising geo-coded 3D coordinate data and related to at least one second scene, said second scene encompassing said first scene, matching the sensor image with the 3D model find a section of the 3D model where there is a match between the first and the second scenes, geo-referencing the sensor image based on the geo-coded 3D coordinate data of the found section of the 3D model, and determining a measure related to an uncertainty in the matching between the sensor image and the 3D model.

Abstract: A method for classifying a terrain type in an area is provided, which method 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. An associated system and computer program product are also provided.

Abstract: A method for classifying a terrain type in an area is provided, which method 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. An associated system and computer program product are also provided.

Abstract: 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.

Abstract: A method for displaying a virtual image of three dimensional objects in an area using stereo recordings of the area for storing a pixel and a height for each point of the area. A method is obtained of enabling displaying of vertical surfaces or even slightly downwards and inwards inclined surfaces. Stereo recordings from at least three different stereo recordings of different solid angles are used. For each different solid angle at least one data base including data about texture and height pixel point wise is established. Data for displaying the virtual image are combined from the different data bases in dependence of the direction in which the virtual image is to be displayed.

Abstract: The present disclosure relates to a method (200) for estimating information related to a vehicle pitch and/or roll angle. The method comprises a step of obtaining (220) a first estimate of the information related to the pitch and/or roll angle. The method is characterized by the steps of capturing (210) an image of an area covering at least a part of the horizon using a camera mounted on the airborne vehicle, and determining (240) an improved estimate of the information related to the pitch and/or roll angle based on the first estimate of the information related to the pitch and/or roll angle, and a digital elevation model.

Abstract: An automated three dimensional mapping method estimating three dimensional models taking advantage of a plurality of images. Positions and attitudes for at least one camera are recorded when images are taken. The at least one camera is geometrically calibrated to indicate the direction of each pixel of an image. A stereo disparity is calculated for a plurality of image pairs covering a same scene position setting a disparity and a certainty measure estimate for each stereo disparity. The different stereo disparity estimates are weighted together to form a 3D model. The stereo disparity estimates are reweighted automatically and adaptively based on the estimated 3D model.

Abstract: 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.

Abstract: 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.

Abstract: The present disclosure relates to a method (200) for estimating information related to a vehicle pitch and/or roll angle. The method comprises a step of obtaining (220) a first estimate of the information related to the pitch and/or roll angle. The method is characterized by the steps of capturing (210) an image of an area covering at least a part of the horizon using a camera mounted on the airborne vehicle, and determining (240) an improved estimate of the information related to the pitch and/or roll angle based on the first estimate of the information related to the pitch and/or roll angle, and a digital elevation model.

Abstract: Various embodiments relate to a method (700) and system for geo-referencing at least one sensor image. The method comprises the steps of: generating at least one sensor image of a first scene with at least one sensor, accessing a 3D model of the environment comprising geo-coded 3D coordinate data and related to at least one second scene, said second scene encompassing said first scene, matching the sensor image with the 3D model find a section of the 3D model where there is a match between the first and the second scenes, geo-referencing the sensor image based on the geo-coded 3D coordinate data of the found section of the 3D model, and determining a measure related to an uncertainty in the matching between the sensor image and the 3D model.

Abstract: The present disclosure relates to a method (1) and system for determining the position of a target. The method comprises a step of measuring (110) 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 (120) 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 (130) with the range and direction measuring device the position of the target relative to the position of the range and direction measuring device.

Abstract: 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.

Abstract: 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.

Abstract: The present invention relates to a method for estimating values for a set of parameters of an imaging system 1. The method comprises taking at least two pictures with the imaging system (1), where the at least two pictures are taken from different positions and where the at least two pictures comprise an at least partially overlapping area. It also comprises sending out pulses to the at least partially overlapping area, and detecting the reflected pulses and calculating distances between a sender of the pulses and the respective point where the pulses were reflected based on the travel time of the pulses. Further, the method comprises associating positioning data to the pictures and to the calculated distance between the points where the pulses were reflected and the sender of the pulses. Said positioning data comprises a position and pointing direction of the imagining system 1 and the sender of the pulses.

Abstract: 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.

Abstract: 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.