No description available.

<p>A laser radar can be used to generate 3D data about the terrain in a very high resolution. The development of new support technologies to analyze these data is critical to the effective and efficient use of these data in decision support systems, due to the large amounts of data that are generated. Adequate technology in this regard is currently not available and development of new methods and algorithms to this end are important goals of this work.</p><p>A semi-qualitative data structure for terrain surface modelling has been developed. A categorization and triangulation process has also been developed to substitute the high resolution 3D model for this data structure. The qualitative part of the structure can be used for detection and recognition of terrain features. The quantitative part of the structure is, together with the qualitative part, used for visualization of the terrain surface. Substituting the 3D model for the semi-qualitative structures means that a data reduction is performed.</p><p>A number of algorithms for detection and recognition of different terrain objects have been developed. The algorithms use the qualitative part of the previously developed semi-qualitative data structure as input. The taken approach is based on matching of symbols and syntactic pattern recognition. Results regarding the accuracy of the implemented algorithms for detection and recognition of terrain objects are visualized.</p><p>A further important goal has been to develop a methodology for determining driveability using 3D-data and other geographic data. These data must be fused with vehicle data to determine the properties of the terrain context of our operations with respect to driveability. This fusion process is therefore called context fusion. The recognized terrain objects are used together with map data in this method. The uncertainty associated with the imprecision of the data has been taken into account as well.</p> / Report code: LiU-Tek-Lic-2008:29.

A laser radar can be used to generate 3D data about the terrain in a very high resolution. The development of new support technologies to analyze these data is critical to the effective and efficient use of these data in decision support systems, due to the large amounts of data that are generated. Adequate technology in this regard is currently not available and development of new methods and algorithms to this end are important goals of this work. A semi-qualitative data structure for terrain surface modelling has been developed. A categorization and triangulation process has also been developed to substitute the high resolution 3D model for this data structure. The qualitative part of the structure can be used for detection and recognition of terrain features. The quantitative part of the structure is, together with the qualitative part, used for visualization of the terrain surface. Substituting the 3D model for the semi-qualitative structures means that a data reduction is performed. A number of algorithms for detection and recognition of different terrain objects have been developed. The algorithms use the qualitative part of the previously developed semi-qualitative data structure as input. The taken approach is based on matching of symbols and syntactic pattern recognition. Results regarding the accuracy of the implemented algorithms for detection and recognition of terrain objects are visualized. A further important goal has been to develop a methodology for determining driveability using 3D-data and other geographic data. These data must be fused with vehicle data to determine the properties of the terrain context of our operations with respect to driveability. This fusion process is therefore called context fusion. The recognized terrain objects are used together with map data in this method. The uncertainty associated with the imprecision of the data has been taken into account as well. / <p>Report code: LiU-Tek-Lic-2008:29.</p>

No description available.

In Geographic Information System (GIS) applications, aster data constitutes one of the major data types. The displaying of the raster data has an important part in GIS applications. Digital Terrain Elevation Data (DTED) is one of the raster data types, which is used as the main data source in this thesis. The DTED data is displayed on the screen as digital images as a pixel value, which is represented in gray scale, corresponding to an elevation (texel). To draw the images, the texel values are mostly interpolated in order to perform zoom-in and/or zoom-out operations on the concerned area. We implement and compare four types of interpolation methods, nearest neighbor, bilinear interpolation, and two new proposed interpolation methods (1) 4-texel weighted average and (2) 8-texel weighted average. The real-time graphical display, with zoom-in/zoom-out capabilities, has also been implemented by buffering DTED data in memory and using a C++ clas that manages graphical operations (zoom-in, zoom-out, and 2D, 3D isplay) by using Windows GDI+ and OpenGL graphic ibraries resulting in 30-40 framesper-second for one grid of DTED Level 0 data.

In this thesis, an unmanned air vehicle (UAV) is used to develop a prototype base test platform for flight testing of new control algorithms and avionics for advanced UAV system development applications. A control system that holds the UAV at a fixed altitude above the ground is designed and flight tested. Only the longitudinal motion of the UAV is considered during the controller design, hence its lateral motions are controlled manually by a remote control unit from the ground. UAV&amp / #8217 / s altitude with respect to the mean sea level and position are obtained by an onboard global positioning system (GPS) and this information is transmitted to the ground computer via radio frequency (RF) communication modules. The altitude of the UAV above the ground is calculated by using the digital terrain elevation data (DTED). A controller is designed and its gains are tuned to maintain this flight altitude at a desired value by using the mathematical model developed to represent the longitudinal dynamics of the UAV. Input signals generated by the controller for elevator deflections are transmitted back to the UAV via RF communication modules to drive onboard servomotors to generate desired elevator deflections. All controller computations and RF communications are handled by a MATLAB&reg / based platform on a ground computer. UAV flight tests are carried out at two different autopilot modes / namely, mean sea level (MSL) altitude hold mode and above ground level (AGL) altitude hold mode. The developed platform worked properly during flight tests and proved to be reliable in almost every condition. Moreover, the designed controller system is demonstrated to be effective and it fulfills the requirements.