Terrain Representation And Reasoning In Computer Generated Forces : A Survey Of Computer Generated Forces Systems And How They Represent And Reason About Terrain

Report on a survey of computer systems used to produce realistic or intelligent behavior by autonomous entities in simulation systems. In particular, it is concerned with the data structures used by computer generated forces systems to represent terrain and the algorithmic approaches used by those systems to reason about terrain

Characteristics of flight simulator visual systems

The physical parameters of the flight simulator visual system that characterize the system and determine its fidelity are identified and defined. The characteristics of visual simulation systems are discussed in terms of the basic categories of spatial, energy, and temporal properties corresponding to the three fundamental quantities of length, mass, and time. Each of these parameters are further addressed in relation to its effect, its appropriate units or descriptors, methods of measurement, and its use or importance to image quality

Rapid Terrain Generation for GeoVisualization, Simulation, Mission Rehearsal, & Operations

Geospecific 3D terrain representation (aka reality modeling) is revolutionizing geovisualization, simulation, and engineering practices around the world. In tandem with the rapid growth in unmanned aerial systems (UAS) and small satellites, reality modeling advancements now allow geospatial intelligence (GEOINT) practitioners to generate three-dimensional models from a decentralized collection of digital images to meet mission needs in both urban and rural environments. Scalable mesh models deliver enhanced, real-world visualization for engineers, geospatial teams, combatant, and combat support organizations. In this, reality modeling provides a detailed understanding of the physical environment, and models allow installation engineers and GEOINT practitioners to quickly generate updated, high-precision 3D reality meshes to provide real-world digital context for the decision-making process

What is a Good Pattern of Life Model? Guidance for Simulations

We have been modeling an ever-increasing scale of applications with agents that simulate the pattern of life (PoL) and real-world human behaviors in diverse regions of the world. The goal is to support sociocultural training and analysis. To measure progress, we propose the definition of a measure of goodness for such simulated agents, and review the issues and challenges associated with first-generation (1G) agents. Then we present a second generation (2G) agent hybrid approach that seeks to improve realism in terms of emergent daily activities, social awareness, and micro-decision making in simulations. We offer a PoL case study with a mix of 1G and 2G approaches that was able to replace the pucksters and avatar operators needed in large-scale immersion exercises. We conclude by observing that a 1G PoL simulation might still be best where large-scale, pre-scripted training scenarios will suffice, while the 2G approach will be important for analysis or if it is vital to learn about adaptive opponents or unexpected or emergent effects of actions. Lessons are shared about ways to blend 1G and 2G approaches to get the best of each

Evaluation of the usefulness of various simulation technology options for TERPS enhancement

Current approved terminal instrument procedures (TERPS) do not permit the full exploitation of the helicopter's unique flying characteristics. Enhanced TERPS need to be developed for a host of non-standard landing sites and navigation aids. Precision navigation systems such as microwave landing systems (MLS) and the Global Positioning System (GPS) open the possibility of curved paths, steep glide slopes, and decelerating helicopter approaches. This study evaluated the feasibility, benefits, and liabilities of using helicopter cockpit simulators in place of flight testing to develop enhanced TERPS criteria for non-standard flight profiles and navigation equipment. Near-term (2 to 5 year) requirements for conducting simulator studies to verify that they produce suitable data comparable to that obtained from previous flight tests are discussed. The long-term (5 to 10 year) research and development requirements to provide necessary modeling for continued simulator-based testing to develop enhanced TERPS criteria are also outlined