• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.9
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• pp.859-866
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• 2008

A guidance scheme for controlling the relative geometry of multiple flight vehicle formation flying is proposed. Each flight vehicle in the formation takes the roles of leader and follower simultaneously except for the formation leader. In this scheme, the flight commands for a leader are shared by all the followers and this leaders to a synchronized flight of all flight vehicles comprising the formation. Lyapunov stability theorem is used to obtain the guidance law. High fidelity nonlinear simulation results are presented to show the effectiveness of the proposed guidance law using a reconnaissance and surveillance mission example.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.125-132
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• 2023

Roundabouts have strengths in traffic flow and safety but can present difficulties for inexperienced drivers. Demand to acquire and analyze drone images has increased to enhance a traffic environment allowing drivers to deal with roundabouts easily. In this paper, we propose a roundabout traffic analysis system that detects, tracks, and analyzes vehicles using a deep learning-based object detection model (YOLOv7) in drone images. About 3600 images for object detection model learning and testing were extracted and labeled from 1 hour of drone video. Through training diverse conditions and evaluating the performance of object detection models, we achieved an average precision (AP) of up to 97.2%. In addition, we utilized SORT (Simple Online and Realtime Tracking) and OC-SORT (Observation-Centric SORT), a real-time object tracking algorithm, which resulted in an average MOTA (Multiple Object Tracking Accuracy) of up to 89.2%. By implementing a method for measuring roundabout entry speed, we achieved an accuracy of 94.5%.

• 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.40 no.6
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• pp.542-547
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• 2012

Until recently, most of GCS(Ground Control Software) has been required to visualize attitude, position, status of vehicle and to transmit control and mission commands for a single UAV(Unmanned Aerial Vehicle). However, the GCS needs to expand its functions to handle more complex situations. Simultaneous operation of multiple UAVs is emerging as a new practice. Hence, we set up requirements for operation of multiple UAVs and suggest the architecture of GCS that satisfy the requirements. In this study, we analyze the upper requirements and define the total structure of GCS at first. Then we design the inner structure for requirements in detail. Finally, we verify the functions of GCS on PILS(Processor In the Loop Simulation) System.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.443-449
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• 2017

Swarm of low-cost UAVs for search mission has benefit in the sense of rapid search compared to use of single high-end UAV. As the number of UAVs forming swarm increases, not only the time for the mission planning increases, but also the system to operate UAVs has excessive burden. This paper addresses a decentralized area search algorithm adequate for multiple UAVs which takes advantages of flexibility, robustness, and simplicity. To down the cost, it is assumed that each UAV has limited ability: close-communication, basic calculation, and limited memory. In close-communication, heath conditions and search information are shared. And collision avoidance and consensus of next search direction are then done. To increase weight on un-searched area and to provide overlapped search, the score function is introduced. Performance and operational characteristics of the proposed search algorithm and mission planning logic are verified via numerical simulations.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.655-662
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• 2022

Recently, with the increase in the use of UAV(unmanned aerial vehicles), research on horizontal maintenance stations that can take off and land in various environments has been actively conducted. These stations can safely land UAV through multiple DOF(degrees of freedom) or at least 2-DOF-based actuator actuation. Among them, many researchers are dealing with the multi-DOF stewart platform due to its high safety. However, the stewart platform requires high-precision control technology because it requires a lot of torque to actuate according to the load action. Therefore, in this paper, to solve the mentioned problem, a bevel gear-based 2-DOF horizontal maintenance station system is proposed. The proposed system is configured to prevent damage due to air resistance when maintaining ships and to install it in a small space. Also, in terms of system configuration, the bevel gear-based horizontal maintenance system has the main advantage of being able to take off and land UAVs of various sizes through the replacement of station pads. The driving of the system consists of a simple form that can control the motor by adjusting the rotation speed of the motor according to the sea waveform.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.238-245
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• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.138-147
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• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.379-399
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• 2020

The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.