• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.3
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• pp.282-287
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• 2015

In modern warfare, the importance of SEAD(Suppression of Enemy Air Defense) mission is being emphasized. However, this mission runs the risk of hull damage or casualties of our friendly air forces. Because of these risks, research on the way of minimizing damages and enhancing mission capability is under active discussion. As a part of this research, SEAD mission planning with multiple UAVs has been covered using vector field guidance. This guidance method not only applies to various forms of flight path but also requires less computational power than other guidance methods. Therefore, in this paper, planning methods of SEAD mission for multiple UAVs using vector field guidance and experimental data from flight experiments regarding designed mission has been covered.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.3
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• pp.229-236
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• 2014

In this paper, the guidance laws and controllers for the gliding guided artillery munition is studied. The gliding guided artillery munition has wings for gliding to increase a range; therefore previous guidance laws and controllers for the guided munition could not be applied. Concepts of vector field guidance and proportional navigation guidance are applied for mid-term and terminal guidance, respectively. The gliding guided artillery munition is operated within wide altitude and speed areas; therefore, the controllers are designed for each area, and gain-scheduling and the linear interpolation technique is applied to compute the appropriate gains.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.981-988
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• 2021

This paper presents a decentralized guidance algorithm for swarm flight of fixed-wing UAVs (Unmanned Aerial Vehicles). Considering swarm flight missions, we assume four representative swarm tasks: gathering, loitering, waypoint/path following, and individual task. Those tasks require several distinct maneuvers such as path following, flocking, and collision avoidance. In order to deal with the required maneuvers, this paper proposes an integrated guidance algorithm based on vector field, augmented Cucker-Smale model, and potential field methods. Integrated guidance command is synthesized with heuristic weights designed for each guidance method. The proposed algorithm is verified through flight tests using up to 19 small fixed-wing UAVs.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.2
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• pp.114-120
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• 2011

This paper presents a cooperative standoff tracking of a moving target using multiple unmanned aircraft. To provide guidance commands, vector fields are designed utilizing the Lyapunov stability theory. A roll angle command is generated to keep a constant distance from the target in a circular motion. A speed command and a heading angle command are designed to keep a constant phase angle with respect to the front aircraft and to prevent a collision between aircraft. Numerical simulation is performed to verify the tracking and collision performance of the proposed control laws.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.117-123
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• 2018

In this study, we suggest a fast image reconstruction scheme using Poisson equation from image gradient domain. In this approach, using the Poisson equation, a guided vector field is created by employing source and target images within a selected region at the first step. Next, the guided vector is used in generating the result image. We analyze the problem of reconstructing a two-dimensional function that approximates a set of desired gradients and a data term. The joined data and gradients are able to work like modifying the image gradients while staying close to the original image. Starting with this formulation, we have a screened Poisson equation known in physics. This equation leads to an efficient solution to the problem in FFT domain. It represents the spatial filters that solve the two-dimensional screened Poisson model and shows gradient scaling to be a well-defined sharpen filter that generalizes Laplace sharpening. We demonstrate the results using a discrete cosine transformation based this Poisson model.