Ground collision avoidance systems on United States Air Force aircraft

Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 1995.Includes bibliographical references (p. 91-92).This thesis examines a specific type of USAF aircraft mishaps - Controlled Flight Into Terrain (CFIT) mishaps. The thesis presents data on CFIT mishaps, causes, and efforts to reduce CFIT mishaps through the development and adoption of Ground Collision Avoidance Systems (GCAS) or similar designs - Ground Proximity Warning Systems (GPWS). GPWS exist today on some USAF aircraft, but many times these systems are inadequate (as evidenced by the continued occurrence of CFIT mishaps). Both ongoing and future initiatives by the USAF to adopt and develop better GPWS/GCAS systems were studied. An analysis was performed which studied the cost to the USAF (and the U.S. taxpayer) as a result of CFIT mishaps, and compared with an analysis of the cost to develop and implement improved GPWS/GCAS systems. The results show conclusively that installing GCAS/GPWS on a majority of USAF aircraft is cost effective. Technology exist today which could improve existing GPWS performance, and although efforts to improve GPWS are moving forward, some resistance does exist. Possible reasons for resistance of GCAS/GPWS adoption were studied and several recommendations were made on how to improve the adoption of these systems within the USAF.by Jan W. Scofield.S.M

Collaborative Workspaces within Distributed Virtual Environments

In warfare, be it a training simulation or actual combat, a commander\u27s time is one of the most valuable and fleeting resources of a military unit. Thus, it is natural for a unit to have a plethora of personnel to analyze and filter information to the decision-maker. This dynamic exchange of ideas between analyst and commander is currently not available within the distributed interactive simulation (DIS) community. This lack of exchange limits the usefulness of the DIS experience to the commander and his troops. This thesis addresses the commander\u27s isolation problem through the integration of a collaborative workspace within AFIT\u27s Synthetic BattleBridge (SBB) as a technique to improve situational awareness. The SBB\u27s Collaborative Workspace enhances battlespace awareness through CSCW (computer supported cooperative work) enabling communication technologies. The SBB\u27s Collaborative Workspace allows the user to interact with other SBB users through the transmission and reception of public bulletins, private email, real-time chat sessions, shared viewpoints, shared video, and shared annotations to the virtual environment. Collaborative communication between SBB occurs through the use of standard and experimental DIS-compliant protocol data units. The SBB\u27s Collaborative Workspace gives the battlespace commander the widest range of communication options available within a DIS virtual environment today

Cruise Missile Integrated Air Defense System Penetration: Modeling the S-400 System

This research determines improved flight-path routes that make maximum utilization of terrain-masking opportunities, and defending radar and missile system equipment performance and launch timing constraints, in order to avoid radar detection and tracking, and to mitigate subsequent missile shoot-down risks. The problem is formulated as one of constrained optimization in three dimensions. Advantageous solutions are identified using the A* Algorithm in conjunction with detailed equipment performance and constraint calculations and high-resolution digital terrain elevation maps. Topographical features in digital terrain are exploited by the algorithm to avoid radar detection and tracking. The model includes provisions for all-aspect/all-frequency radar cross section variations, radar horizon masking, and specific factors relevant to the TLAM BGM-109 cruise missile and the Russian S-400 long-range and Pantsir point-defense IADS systems. Research conclusions indicate that intelligent exploitation of modeled system technical and performance capabilities and limitations yields improved survivability in conjunction with, and supplementing, terrain masking

Stealthy River Navigation in Jungle Combat Conditions

One of the biggest challenges for Brazilian military logisticians is to support effective jungle warfare for both real and training operations carried out by their combat forces in the Amazonian region. The jungle\u27s heat, humidity, and dense vegetation put significant demands on the supply chain. Further, because of the difficulties of land or air transportation, water transport is the most reasonable transportation option to sustain these deployed forces. Planners must select from among the available watercourses those whose surroundings provide stealthy navigation to the combat force location where the requested supplies can be safely unloaded. We seek a method of determining a path through a river network that blends short transit times with maximal shade coverage from forest growth along the riverbanks. We combine an astronomical algorithm for computing shadow coverage with Dijkstra\u27s shortest path algorithm to determine the start time and routing information necessary for a supply boat to travel from a depot to a resupply point that minimizes weighted risk, which is defined as the product of shade coverage and arc transit time

Design of Environment Aware Planning Heuristics for Complex Navigation Objectives

A heuristic is the simplified approximations that helps guide a planner in deducing the best way to move forward. Heuristics are valued in many modern AI algorithms and decision-making architectures due to their ability to drastically reduce computation time. Particularly in robotics, path planning heuristics are widely leveraged to aid in navigation and exploration. As the robotic platform explores and navigates, information about the world can and should be used to augment and update the heuristic to guide solutions. Complex heuristics that can account for environmental factors, robot capabilities, and desired actions provide optimal results with little wasted exploration, but are computationally expensive. This thesis demonstrates results of research into simplifying heuristics that maintains the performance improvements from complicated heuristics. The research presented is validated on two complex robotic tasks: stealth planning and energy efficient planning. The stealth heuristic was created to inform a planner and allow a ground robot to navigate unknown environments in a less visible manner. Due to the highly uncertain nature of the world (where unknown observers exist) this heuristic implemented was instrumental to enabling the first high-uncertainty stealth planner. Heuristic guidance is further explored for use in energy efficient planning, where a machine learning approach is used to generate a heuristic measure. This thesis demonstrates effective learned heuristics that simplify convergence time and accounts for the complexities of environment. A reduction of 60% in required compute time for planning was found

Feasibility analysis study of battlefield distributed simulation - developmental (BDS-D) Version 1.0 system testbed extension : Fidelity and verification validation and accreditation

Issued as Report, Project E-16-M96 (subproject: A-9606)Report has title: Feasibility analysis study of battlefield distributed simulation - developmental (BDS-D) Version 1.0 system testbed extension : Fidelity and verification validation and accreditatio

ENSURING SURVIVABILITY FOR NAVAL SPECIAL WARFARE OPERATIONS IN THE ARCTIC

Naval Special Warfare (NSW) operators are not currently manned, trained, or equipped to effectively survive or execute High Arctic mission sets. The dynamic rate of environmental change and the adversarial exploitation of the Arctic regions have disadvantaged the United States and its allies. This capstone intends to reduce inherent survival risks an NSW operator would incur associated with extreme “cold” and increase the duration an NSW operator can remain on station in the High Arctic. The end state is to provide NSW with research and a Course of Action (COA) that leads to prototype production, orchestrated through the Defense Innovation Unit (DIU), enabling NSW operators to rapidly respond to crisis/conflict in all Arctic regions.Lieutenant, United States NavyApproved for public release. Distribution is unlimited

TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation

Effective use of camera-based vision systems is essential for robust performance in autonomous off-road driving, particularly in the high-speed regime. Despite success in structured, on-road settings, current end-to-end approaches for scene prediction have yet to be successfully adapted for complex outdoor terrain. To this end, we present TerrainNet, a vision-based terrain perception system for semantic and geometric terrain prediction for aggressive, off-road navigation. The approach relies on several key insights and practical considerations for achieving reliable terrain modeling. The network includes a multi-headed output representation to capture fine- and coarse-grained terrain features necessary for estimating traversability. Accurate depth estimation is achieved using self-supervised depth completion with multi-view RGB and stereo inputs. Requirements for real-time performance and fast inference speeds are met using efficient, learned image feature projections. Furthermore, the model is trained on a large-scale, real-world off-road dataset collected across a variety of diverse outdoor environments. We show how TerrainNet can also be used for costmap prediction and provide a detailed framework for integration into a planning module. We demonstrate the performance of TerrainNet through extensive comparison to current state-of-the-art baselines for camera-only scene prediction. Finally, we showcase the effectiveness of integrating TerrainNet within a complete autonomous-driving stack by conducting a real-world vehicle test in a challenging off-road scenario

Design of an Agile Unmanned Combat Vehicle - A Product of the DARPA UGCV Program

The unmanned ground combat vehicle (UGCV) design evolved by the SAIC team on the DARPA UGCV Program is summarized in this paper. This UGCV design provides exceptional performance against all of the program metrics and incorporates key attributes essential for high performance robotic combat vehicles. This performance includes protection against 7.62 mm threats, C130 and CH47 transportability, and the ability to accept several relevant weapons payloads, as well as advanced sensors and perception algorithms evolving from the PerceptOR program. The UGCV design incorporates a combination of technologies and design features, carefully selected through detailed trade studies, which provide optimum performance against mobility, payload, and endurance goals without sacrificing transportability, survivability, or life cycle cost. The design was optimized to maximize performance against all Category I metrics. In each case, the performance of this design was validated with detailed simulations, indicating that the vehicle exceeded the Category I metrics. Mobility metrics were analyzed using high fidelity VisualNastran vehicle models, which incorporate the suspension control algorithms and controller cycles times. DADS/Easy 5 3-D models and ADAMS simulations were also used to validate vehicle dynamics and control algorithms during obstacle negotiation