• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.64-72
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• 2021

Manned-unmanned teaming can be a very promising air-to-air combat tactic since it can maximize the advantage of combining human insight with the robustness of the machine. The rapid advances in artificial intelligence and autonomous control technology will speed up the development of manned-unmanned teaming air-to-air combat system. In this paper, we introduce a manned-unmanned teaming air-to-air combat tactic which is composed of a manned aircraft and an UAV. In this tactic, a manned aircraft equipped with radar is functioning both as a sensor to detect the hostile aircraft and as a controller to direct the UAV to engage the hostile aircraft. The UAV equipped with missiles is functioning as an actor to engage the hostile aircraft. We also developed a combat scenario of executing this tactic where the manned-unmanned teaming is engaging a hostile aircraft. The hostile aircraft is equipped with both missiles and radar. To demonstrate the efficiency of the tactic, we run the simulation of the scenario of the tactic. Using the simulation, we found the optimal formation and maneuver for the manned-unmanned teaming where the manned-unmanned teaming can survive while the hostile aircraft is shot-downed. The result of this study can provide an insight to how manned aircraft can collaborate with UAV to carry out air-to-air combat missions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.1
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• pp.10-19
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• 2022

Recently, the Defense Advanced Research Projects Agency(DARPA) in the United States is studying a new concept of war called Mosaic Warfare, and MUM-T(Manned-Unmanned Teaming) through the division of missions between expensive manned and inexpensive unmanned aircraft is at the center. This study began with the aim of deriving the priority of autonomous functions according to the role of unmanned aerial vehicles in the present and present collaboration that is emerging along with the concept of mosaic warfare. The autonomous function of unmanned aerial vehicles between the presence and absence collaboration may vary in priority depending on the tactical operation of unmanned aerial vehicles, such as air-to-air, air-to-ground, and surveillance and reconnaissance. In this paper, ACE (Air Combat Evaluation), Skyborg, and Longshot, which are recently studied by DARPA, derive the priority of autonomous functions according to air-to-air collaboration, and use AHP analysis. The results of this study are meaningful in that it is possible to recognize the priorities of autonomous functions necessary for unmanned aircraft in order to develop unmanned aerial vehicles according to the priority of autonomous functions and to construct a roadmap for technology implementation. Furthermore, it is believed that the mass production and utilization of unmanned air vehicles will increase if one unmanned air vehicle platform with only essential functions necessary for air-to-air, air-to-air, and surveillance is developed and autonomous functions are expanded in the form of modules according to the tactical operation concept.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.3
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• pp.199-212
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• 2014

This paper describes an autonomous air combat guidance law using a Virtual Pursuit Point (VPP) in one-on-one close engagement for Unmanned Combat Aerial Vehicle (UCAV). The VPPs that consist of virtual lag and lead points are introduced to carry out tactical combat maneuvers. The VPPs are generated based on fighter's aerodynamic performance and Basic Fighter Maneuver (BFM)'s turn circle, total energy and weapon characteristics. The UCAV determines a single VPP and executes pursuit maneuvers based on a smoothing function which evaluates probabilities of the pursuit types for switching maneuvers with given combat states. The proposed law is demonstrated by high-fidelity real-time combat simulation using commercial fighter model and X-Plane simulator.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.24-34
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• 2011

An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for human. UA V s are currently employed in many military missions such as reconnaissance, surveillance, enemy radar jamming, decoying, suppression of enemy air defense (SEAD), fixed and moving target attack, and air-to-air combat. UAVs also are employed in a number of civilian applications such as monitoring ozone depletion, inclement weather, traffic congestion, and taking images of dangerous territory. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$-PGA (A-star with Post Smoothing-Parallel Genetic Algorithm) for an UAV's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and TSP (Traveling Salesman Problem). A path planning algorithm for UAV is applied by transforming MRPP into SPP (Shortest Path Problem).

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.315-323
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• 2016

This paper deals with experimental investigation of active flow control via synthetic jets using an unmanned combat air vehicle (UCAV) planform. Fourteen arrays of synthetic jets, mounted along both leading edges, were fully or partially activated to increase aerodynamic efficiency and reduce pitch-up moment. The measurements were carried out using a six-component external balance, a pressure scanner, and tuft flow visualization. It was observed that aerodynamic efficiency (L/D) and pitching moment were clearly affected by the location of jets. In particular, inboard and outboard actuation could effectively increase L/D. Moreover, inboard actuation showed a reduction in the pitch-up, even more than that generated by the full actuation. These results suggest that inboard actuation not only effectively increases L/D but also reduces the pitch-up using only a few actuators.

• Journal of computational fluids engineering
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• v.17 no.4
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• pp.56-68
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• 2012

Nowadays, Unmanned Combat Air Vehicle(UCAV) has become an important aircraft system for the national defense. For its efficiency and survivability, shape optimization of UCAV is an essential part of its design process. In this paper, shape optimization of UCAV was processed for aerodynamic performance improvement and Radar Cross Section(RCS) reduction using Multi Objective Genetic Algorithm(MOGA). Lift and induced drag, friction drag, RCS were calculated using panel method, boundary layer theory, Physical Optics(PO) approximation respectively. In particular, calculation applied Radar Absorbing Material(RAM) was performed for the additional RCS reduction. Results are indicated that shape optimization is performed well for improving aerodynamic performance, reducing RCS. Further study will be performed with higher fidelity tools and consider other design segments including structure.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.554-559
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• 2016

본 논문은 EDISON CFD를 사용하여 스포일러가 장착된 무미익 BWB UCAV에 대하여 이차원 유동해석을 수행하였다. 무미익 형상은 일반적인 항공기보다 롤과 요 방향의 안정성과 조성성에 있어 불리한 특징을 갖는데 특히 이 착륙 시 고 받음각의 영역에서 발생하는 Pitch-up 현상이 항공기 안정성에 문제를 야기한다. 수직 미익 부재와 pitch-up 현상으로 인한 BWB형상의 UCAV가 지니는 단점을 보완하기 위해서 스포일러가 장착된 형상이 적용되기도 한다 본 연구에서는 윗면과 아랫면에 스포일러가 장착된 경우에 대해 전산유동해석을 수행하였다. 해석결과 윗면의 스포일러는 양력의 감소와 항력의 증가를 야기했으며, 아랫면의 스포일러는 양력과 항력을 모두 증가시켰다. 피칭모멘트의 경우 아랫면의 스포일러가 저받음각에서 안정성을 증가시켰다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.299-304
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• 2023

Recently, drones have been used as a major means of attack drones in major wars around the world, and it seems likely that they will evolve into game changers in the future. Recently, drones have been used as a major means of attack drones in major wars around the world, and it seems likely that they will evolve into game changers in the future. In the major wars of the 21century, attack drones are used for precision fire-guided or self-destruct attacks, For the purpose of cognitive warfare, its territory is expanding not only to land and air, but also to sea and water. These attack drones will perform multi-domain operations, and for this purpose, the level of autonomy will be improved and High-Low Mix We will continue to develop by strengthening concept-based scalability. North Korea has also been making considerable efforts to operate attack drones for a long time, and activities such as third-country-level self-explosive drones, artificial intelligence-based clustered self-explosive drones, and self-destructive stealth unmanned semi-submersible are expected. In addition to North Korea's provocations and attacks, it is hoped that there will be a need for active follow-up research on our military's countermeasures and utilization plans.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.936-939
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• 2022

As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.12
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• pp.1084-1093
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• 2017

As the survivability of an aircraft in the battlefield becomes a critical issue, there is a growing need to improve the survivability of the aircraft. In this study, the survivability of an UCAV associated with plume IR signature was investigated. In order to analyze the survivability of the aircraft, the lock-on range and the lethal envelope, defined as the IR detection distance of the aircraft and the range of shooting down by the missile, respectively, were first introduced. Further, a method to calculate the lethal envelope for the scenario of surface-to-air missiles including the vertical plane was developed. The study confirmed that the red zone of an UCAV shows a substantial difference in the zone size as well as the characteristics in the upward and downward directions.