• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.114-123
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• 2016

The effective feature extraction method for unmanned aerial vehicle (UAV) detection is proposed and verified in this paper. The UAV engine sound is harmonic complex tone whose frequency ratio is integer and its variation is continuous in time. Using these characteristic, we propose the feature vector composed of a mean and standard deviation of difference value between fundamental frequency with 1st overtone as well as mean variation of their frequency. It was revealed by simulation that the suggested feature vector has excellent discrimination in target signal identification from various interfering signals including frequency variation with time. By comparing Fisher scores, three features based on frequency show outstanding discrimination of measured UAV signals with low signal to noise ratio (SNR). Detection performance with simulated interference signal is compared by MFCC by using ELM classifier and the suggested feature vector shows 37.6% of performance improvement As the SNR increases with time, the proposed feature can detect the target signal ahead of MFCC that needs 4.5 dB higher signal power to detect the target.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.10-20
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• 2019

Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.27-33
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• 2020

Recently, visual object detection and tracking has become a vital role in many different applications. It spans various applications like robotics, video surveillance, and intelligent vehicle navigation. Especially, in current situation where the use of UAVs is expanding widely, detection and tracking to soot down illegal UAVs flying over the sky at airports, nuclear power plants and core facilities is becoming a very important task. The remarkable method in object tracking is correlation filter based tracker like KCF (Kernelized Correlation Filter). But it has problems related to target drift in tracking process for long-term tracking. To mitigate the target drift problem in video surveillance application, we propose a tracking method which uses KCF, adaptive thresholding and Kalman filter. In the experiment, the proposed method was verified by using monochrome video sequences which were obtained in the operational environment of UAV.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.152-163
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• 2022

In this paper, we present a method to enable an unmanned aerial vehicle to drop the sonobuoy, an essential element of anti-submarine warfare, in an optimal deployment. To this end, an environment simulating the distribution of sound detection performance was configured through the Unity game engine, and the environment directly configured using Unity ML-Agents and the reinforcement learning algorithm written in Python from the outside communicated with each other and learned. In particular, reinforcement learning is introduced to prevent the accumulation of wrong actions and affect learning, and to secure the maximum detection area for the sonobuoy while the vehicle flies to the target point in the shortest time. The optimal placement of the sonobuoy was achieved by applying the Deep Deterministic Policy Gradient (DDPG) algorithm. As a result of the learning, the agent flew through the sea area and passed only the points to achieve the optimal placement among the 70 target candidates. This means that an autonomous aerial vehicle that deploys a sonobuoy in the shortest time and maximum detection area, which is the requirement for optimal placement, has been implemented.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.668-673
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• 2007

We propose the design of the warfighting experiment process for software intensive systems using the intelligent maturity model and suggest the application results of the target searching capability in smart UAV. For this, we design the intelligent maturity model to evaluate the intelligent degree of the software intensive systems considering the domain and intelligent level. Then we classify the IS0/1EC-12207 process and CMMI process as LITO domain for designing the warfighting experiment process, map the classifed process to the five factors of the warfighting experiment and derive the process as warfighting experiment element and phase. Based on the derived process, we design the warfighting experiment process using the IDEF0. Finally we apply the proposed process to the target search capability and suggest the results which are required to develop and acquire the smart UAV.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.225-232
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• 2014

In this study, a cooperative UAV and UGV platform is proposed to obtain a wide range of visual information. The UAV recognizes a pattern marker on UGV and tracks the UGV without user control. It can provide wide range of visual information for a user in the UGV. The UGV by a user is controled equipped with an aluminum board. And the UAV can take off and land on the UGV. The UAV uses two cameras; one camera is used to recognize a pattern marker and another is used to provide a wide range of visual information to the UGV's user. It is guaranteed that the proposed visual-based approach detects and tracks the target marker on the UGV, and then lands well. The experimental results show that the proposed approach can effectively construct a cooperative UAV/UGV platform for obtaining a wide range of vision information.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.312-318
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• 2022

Currently, the Republic of Korea is facing the problem of a decrease in military service resources due to the demographic cliff, and is pursuing military restructuring and changes in the military force structure in order to respond to this. In this situation, the Army is pushing forward the deployment of a drone-bot combat system that will lead the future battlefield. The battlefield of the future will be changed into an integrated battlefield concept that combines command and control, surveillance and reconnaissance, and precision strike. According to these changes, unmanned combat system, including dronebots, will be widely applied to combat situations that are high risk and difficult for humans to perform in actual combat. In this paper, as one of the countermeasures to these changes, autonomous behavior software with a BDI architecture-based decision-making system was developed. The autonomous behavior software applied a framework structure to improve applicability to multiple models. Its function was verified in a PC-based environment by assuming that the target UAV is a battalion-level surveillance and reconnaissance UAV.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.11-22
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• 2017

In recent years, coastal dune erosion has accelerated as various structures have been developed around the coastal dunes. A land cover map should be developed to identify the characteristics of sand dunes and to monitor the condition of sand dunes. The Korean Ministry of Environment's land cover maps suffer from problems, such as limited classes, target areas, and durations. Thus, this study conducted experiments using RGB and multispectral images based on UAV (Unmanned Aerial Vehicle) over an approximately one-year cycle to create a land cover map of coastal dunes. RF (Random Forest) classifier was used for the analysis in accordance with the experimental region's characteristics. The pixel- and object-based classification results obtained by using RGB and multispectral cameras were evaluated, respectively. The study results showed that object-based classification using multispectral images had the highest accuracy. Our results suggest that constant monitoring of coastal dunes can be performed effectively.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.4
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• pp.117-124
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• 2015

RAM (Reliability, Availability and Maintenance) has been applied to design and analysis tools which affects system's operational sustainability and its life cycle cost as RAM-c(2009 DoD). RAM-c plays also an important role to guarantee the system engineering for mission assurance. Reliability is highly related to the probability of system failure. Availability means mission capability or the condition of ready to mission. Maintenance includes both the repair to recover the system in the event of failure/unexpected breakdown and proactive maintenance to prolong the design service life of the system or machinery. It is the purpose that this paper is to analyze and conclude the objective service life of UAV. The more UAV is operated, the less the level of its reliability becomes. Repairing failures and supplying spare parts on time, system reliability could be improved up until the time over target. Applying statistical Weibull distributions, this paper suggests the analysis of the design service life and economic life of UAV based on RAM-c with operational data.

• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.405-412
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• 2013

Purpose: In this paper, the improvement of the image quality is investigated. The image quality is degraded by the drift phenomenon of EO/IR (Electro-Optical/Infrared) device on UAV. The drift phenomenon means that the image of EO/IR equipment on UAV(Unmanned Aerial Vehicle) moves to the unintended direction. This phenomenon should be improved for successful flight mission. Methods: To improve the drift phenomenon, the drift compensation method, the combination algorithm of FMC(Forward Motion Compensation) and AMC(Angular Motion Compensation) method, are introduced to calculate pitch and azimuth angle. Result values of pitch and azimuth angle are used for the improvement of image quality in EO/IR control logic. Results: The image quality is quantitatively improved more than 15 times through field test data of flight. Conclusion: Using the drift compensation technique, the image quality for EO/IR equipment is improved over 15 times than existing methods. This means the user of UAV with EO/IR device can perform a successful mission by keeping the line of sight for the target accurately.