No abstract

A hierarchical and automated control strategy applicable to the typical suppression of enemy air defense missions that involve multiple unmanned aerial vehicles is addressed. The new path finding and planning method is based upon the potential field theory, whereas conventional approaches largely rely on the so-called Voronoi diagram. The potential field approach that has been widely used for robot path planning is modified into the suppression of enemy air defense maneuver satisfying various mission objectives. In particular, cooperative maneuvers of unmanned aerial vehicles to attack a common target are dealt with successfully by the proposed potential field approach. A simultaneous arrival condition from different departure points is satisfied by seeking a different set of candidate solutions for the given potential field. Despite increased numerical computational workload in the new method, it leads to significant advantages with smooth trajectory as illustrated by battlefield simulation results.

In recent years, there is a growing interest in employing Unmanned Combat Air Vehicles (UCAVs) for various military missions. One of typical examples is the suppression of Enemy Air Defense (SEAD) mission, in which the objective is to fly to the enemy territory to destroy, or suppress surface-based air defenses such as radars and surface-to-air missile sites. This paper deals with a hierarchical and fully automated control scheme which is suitable to typical SEAD mission using multiple UCAVs. For the path finding and planning, most of the existing control scheme use the Voronoi-diagram concept, but a new path planning method which is based on the potential field concept is proposed. The advantages and disadvantages of existing method and a new method are presented with virtual battle field simulation results.

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5% per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport -Collaborative Decision Making) or S-CDM(Surface -Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte/Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration -2 (ATD-2) project for technology demonstration of Integrated Arrival/Departure/Surface (ADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement)/KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

A nonlinear aircraft tracking filter using a point mass flight dynamics model with three degrees of freedom is presented. While the models used by conventional air traffic control tracking filters are based on simple kinematics, the model for the present filter is based not only on kinematic relations but also on three-dimensional aircraft translational force equations and control variables. This allows for practical and sophisticated implementation of the attitude effects on translational acceleration. The control variables, which consist of the angle of attack, roll angle, and thrust setting, are treated as states with random processes. Tracking with simulation data indicates that the present filter is superior to other single and multiple model-based filters in terms of position and course accuracy, and the model associated with it is insensitive to flight motion types and design parameters. The results of tracking with real flight data also correspond well with those found by tracking with the simulation data.