Urban activities involving planning, preparing for and responding to time critical situations often demands sound situational awareness of overall settings. Decision makers, who are tasked to respond effectively to emergencies, must be equipped with information on the details of what is happening, and must stay informed with updates as the event unfolds and remain attentive to the extent of impact the dynamics of the surrounding settings might have. Recent increases in the volumes of geo-spatial data such as satellite imageries, elevation maps, street-level photographs and real-time imageries from remote sensory devices affect the way decision makers make assessments in time-critical situations. When terrain related spatial information are presented accurately, timely, and are augmented with terrain analysis such as viewshed computations, enhanced situational understanding could be formed. Painting such enhanced situational pictures, however, demands efficient techniques to process and present volumes of geo-spatial data. Modern Graphics Processing Units (GPUs) have opened up a wide field of applications far beyond processing millions of polygons. This dissertation presents approaches that harness graphics rendering techniques and GPU programmability to visualize urban terrain with accuracy, viewshed analysis and real-time imageries. The GPU ray tracing and image fusion visualization techniques presented herein have the potential to aid in achieving enhanced urban situational awareness and understanding. Current state of the art polygon based terrain representations often use coarse representations for terrain features of less importance to improve rendering rate. This results in reduced geometrical accuracy for selective terrain features that are considered less critical to the visualization or simulation needs. Alternatively, to render highly accurate urban terrain, considerable computational effort is needed. A compromise between achieving real-time rendering rate and iv accurate terrain representations would have to be made. Likewise, computational tasks involved in terrain-related calculations such as viewshed analysis are highly computational intensive and are traditionally performed at a non-interactive rate. The first contribution of the research involves using GPU ray tracing, a rendering approach, conventionally not employed in the simulation community in favor of rasterization, to achieve accurate visualization and improved understanding of urban terrain. The efficiency of using GPU ray tracing is demonstrated in two areas, namely, in depicting complex, large scale terrain and in visualizing viewshed terrain effects at interactive rate. Another contribution entails designing a novel approach to create an efficient and real-time mapping system. The solution achieves updating and visualizing terrain textures using 2D georeferenced imageries for enhanced situational awareness. Fusing myriad of multi-view 2D inputs spatially for a complex 3D urban scene typically involves a large number of computationally demanding tasks such as image registrations, mosaickings and texture mapping. Current state of the art solutions essentially belongs to two groups. Each strives to either provide near real-time situational pictures in 2D or off-line complex 3D reconstructions for subsequent usages. The solution proposed in this research relies on using prior constructed synthetic terrains as backdrops to be updated with real-time geo-referenced images. The solution achieves speed in fusing information in 3D. Mapping geo-referenced images spatially in 3D puts them into context. It aids in conveying spatial relationships among the data. Prototypes to evaluate the effectiveness of the aforementioned techniques are also implemented. The benefits of augmenting situational displays with viewshed analysis and real-time geo-referenced images in relation to enhancing the user's situational awareness are also evaluated. Preliminary results v from user evaluation studies demonstrate the usefulness of the techniques in enhancing operators' performances, in relation to situational awareness and understanding.

No description available.

No description available.

Modern air battles are very dynamic and fast, and put extreme pressure on pilots. In some unpredictable situations, like new discovered threats or mission plan deviation because of enemy aircraft, the pilots might need to replan their predefined flight route. This is very difficult, if not impossible, to do since numerous factors affect it. A system that can help the pilots to do such a thing is needed. P revious work in this field has involved methods from artificial intelligence like A*-search. In this master thesis, implementation of a replanning system based on a control theory method, Model Predictive Control (MPC), is examined. Different factors influencing the path, such as terrain and threats, are included in the algorithm. The results presented in this thesis show that MPC solves the problem. As with every method there are some drawbacks and advantages, but as a summary the method is a very promising one and is worth further development. Proposals of future work and different improvements of the algorithms used here are presented in this report as well.

<p>Modern air battles are very dynamic and fast, and put extreme pressure on pilots. In some unpredictable situations, like new discovered threats or mission plan deviation because of enemy aircraft, the pilots might need to replan their predefined flight route. This is very difficult, if not impossible, to do since numerous factors affect it. A system that can help the pilots to do such a thing is needed. P</p><p>revious work in this field has involved methods from artificial intelligence like A*-search. In this master thesis, implementation of a replanning system based on a control theory method, Model Predictive Control (MPC), is examined. Different factors influencing the path, such as terrain and threats, are included in the algorithm. </p><p>The results presented in this thesis show that MPC solves the problem. As with every method there are some drawbacks and advantages, but as a summary the method is a very promising one and is worth further development. </p><p>Proposals of future work and different improvements of the algorithms used here are presented in this report as well.</p>

No description available.

No description available.

No description available.

Synthetic Vision Systems (SVS) provide an aircraft pilot with a virtual 3-D image of surrounding terrain which is generated from a digital elevation model stored in an onboard database. SVS improves the pilot's situational awareness at night and in inclement weather, thus reducing the chance of accidents such as controlled flight into terrain. A terrain database integrity monitor is needed to verify the accuracy of the displayed image due to potential database and navigational system errors. Previous research has used existing aircraft sensors to compare the real terrain position with the predicted position. We propose an improvement to one of these models by leveraging the stream computing capabilities of commercial graphics hardware. "Brook for GPUs," a system for implementing stream computing applications on programmable graphics processors, is used to execute a streaming ray-casting algorithm that correctly simulates the beam characteristics of a radar altimeter during all phases of flight.