• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.2
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• pp.152-160
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• 2008

In the present paper, a transonic mixed-flow compressor that has relatively lower frontal area than that of centrifugal compressors is discussed, and aerodynamic design as well as performance prediction are performed. Main design constraints are compressor exit Mach number of 0.3 and flow angle of 30degrees at the design point, and maximum overall compressor diameter of 177mm, that is 7.0inch. The mass flow rate of design point and pressure ratio are 1.05kg/s and 5.2:1, respectively. The aerodynamic design results show that the transonic compressor designed with forward-swept inducer and curved diffuser can have the target performance with efficiency of 75% within the given constraints. And the compressor exit flow characteristics are discussed here.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.829-842
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• 2018

Unmanned Aerial Vehicle (UAV) is diversely utilized in our lives such as daily hobbies, specialized video image taking and disaster prevention activities. New ways of UAV application have been explored recently such as UAV-based delivery. However, most UAV systems are being utilized in a passive form such as real-time video image monitoring, filmed image ground analysis and storage. For more proactive UAV utilization, there should be higher-performance UAV and large-capacity memory than those presently utilized. Against this backdrop, this study described the general matters on proactive software platform and high-performance UAV hardware for real-time target tracking; implemented research on its design and implementation, and described its implementation method. Moreover, in its established platform, this study measured and analyzed the core-specific CPU consumption.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.14-29
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• 2020

The 6G mobile communication system will become a backbone infrastructure around 2030 for the future digital world by providing distinctive services such as five-sense holograms, ultra-high reliability/low-latency, ultra-high-precision positioning, ultra-massive connectivity, and gigabit-per-second data rate for aerial and maritime terminals. The recent remarkable advances in machine learning (ML) technology have recognized its efficiency in wireless networking fields such as resource management and cell-configuration optimization. Further innovation in ML is expected to play an important role in solving new problems arising from 6G network management and service delivery. In contrast, an approach to apply ML to a physical-layer (PHY) target tackles the basic problems in radio links, such as overcoming signal distortion and interference. This paper reviews the methodologies of ML-based PHY, relevant industrial trends, and candiate technologies, including future research directions and standardization impacts.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.180-187
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• 2007

In this paper, we propose an automatic method which combines two or more images acquired by camera on the air-vehicle into a larger image mosaics. The shift, scaling, rotation factors between two images can be calculated by using the correspondences between the points of the images. In order to estimate these factors, we find the relative positions of two images with respect to each other by using the SIFT descriptor and the RANSAC algorithm. After estimating the factors, the images can be merged into a single image mosaic by warping the target image. To avoid seams when mosaics are constructed from overlapped images, we apply the average gray level value of points within a overlapped zone. We have tested our proposed method on various image sets and have confirmed that our method produced good result subjectively.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.4
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• pp.227-232
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• 2018

In this paper, we propose a faster object detection and tracking method using Deep Learning, UAV(unmanned aerial vehicle), Kalman filter and YOLO(You Only Look Once)v3 algorithms. The performance of the object tracking system is decided by the performance and the accuracy of object detecting and tracking algorithms. So we applied to the YOLOv3 algorithm which is the best detection algorithm now at our proposed detecting system and also used the Kalman Filter algorithm that uses a variable detection area as the tracking system. In the experiment result, we could find the proposed system is an excellent result more than a fixed area detection system.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.122-129
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• 2021

For the Simultaneous Localization and Mapping (SLAM) problem, a different path results in different SLAM results. Usually, SLAM follows a trail of input data. Active SLAM, which determines where to sense for the next step, can suggest a better path for a better SLAM result during the data acquisition step. In this paper, we will use reinforcement learning to find where to perceive. By assigning entire target area coverage to a goal and uncertainty as a negative reward, the reinforcement learning network finds an optimal path to minimize trajectory uncertainty and maximize map coverage. However, most active SLAM researches are performed in indoor or aerial environments where robots can move in every direction. In the urban environment, vehicles only can move following road structure and traffic rules. Graph structure can efficiently express road environment, considering crossroads and streets as nodes and edges, respectively. In this paper, we propose a novel method to find optimal SLAM path using graph structure and reinforcement learning technique.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.173-179
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• 2022

The satellite navigation deception technology disturbs the navigation solution of the receiver by generating a deceptive signal simulating the actual satellite for the satellite navigation receiver mounted on the unmanned aerial vehicle, which is the target of deception. A single spoofing technique that creates a single deceptive position and velocity can be divided into a synchronized spoofing signal that matches the code delay, Doppler frequency, and navigation message with the real satellite and an unsynchronized spoofing signal that does not match. In order to generate a signal synchronized with a satellite signal, a very sophisticated and high precision signal generation technology is required. In addition, the current position and speed of the UAV equipped with the receiver must be accurately detected in real time. Considering the detection accuracy of the current radar technology that detects small UAVs, it is difficult to detect UAVs with an accuracy of less than one chip. In this paper, we assume the asynchrony of a single spoofing signal and propose a region defense technique using multiple spoofing signals.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.15-22
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• 2003

This study aims to construct a management system of road position information as part of the build-up to a maintenance and management system of highways. First, information on the positions of the roads were obtained by a real-time kinematic satellite surveying, and then the degree of accuracy was analyzed in comparison with the data of the existing design drawings. The linear coordinates of road center line obtained by using RTK GPS showed about 7.6-13.2cm errors in X and Y directions in the case of the national road No.2 section, and about 8.4-9.2cm errors in the case of local road No.1045 section. These errors were within the tolerance scope regulated by the TS survey, and could be practically used. In the case of vertical alignment, there were about 6.2cm errors in the Z direction in local road No.1045 section. Aerial photographs are normally used in producing numerical maps, and it can be practically used because the tolerance scope of the elevation control point is l0cm when the scale of aerial photographs is 1/1000. The management system of road position information, utilizing Object-Oriented Programming(OOP), was built having the data acquired in this way as the attribute data. The system developed in this way can enable us to spot the positions of road facilities, the target of management with ease, to easily update the data in case of changes in the positions of roads and road facilities, and to manage the positions of roads and road facilities more effectively.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.55-62
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• 2013

This paper aims to detect Speed Bump by using Omni-directional Camera and to suggest Real-time update scheme of Speed Bump through Vision Based Approach. In order to detect Speed Bump from sequence of camera images, noise should be removed as well as spot estimated as shape and pattern for speed bump should be detected first. Now that speed bump has a regular form of white and yellow area, we extracted speed bump on the road by applying erosion and dilation morphological operations and by using the HSV color model. By collecting huge panoramic images from the camera, we are able to detect the target object and to calculate the distance through GPS log data. Last but not least, we evaluated accuracy of obtained result and detection algorithm by implementing SLAMS (Simultaneous Localization and Mapping system).

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.469-479
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• 2016

Kimchi cabbage is one of the most important vegetables in Korea and a target crop for market stabilization as well. In particular Kimchi cabbages in a highland area are very sensitive to the fluctuations in supply and demand. Yield variability due to growth conditions dictates the market fluctuations of Kimchi cabbage price. This study was carried out to understand the distribution of the highland Kimchi cabbage growth status in Anbandeok. Anbandeok area in Gangneung, Gangwon-do, Korea is one of the main producing districts of highland Kimchi cabbage. The highland Kimchi cabbage status map of each growth factor was obtained from unmanned aerial vehicle (UAV) imagery and field survey data. Six status maps include UAVRGB image map, normalized difference vegetation index (NDVI) distribution/anomaly map, Crop distribution map, Planting/Harvest distribution map, Growth parameter map and Growth disorder map. As a result, the highland Kimchi cabbage status maps from May 31 to Sep. 6 in 2016 were presented to show spatial variability in the field. The benefits of the highland Kimchi cabbage status map can be summarized as follows: crop growth monitoring, reference for field observations and survey, the relative comparison of the growth condition in field scale, evaluation of growth in comparison of average year, change detection of annual crops or planting areas, abandoned fields monitoring, prediction of harvest season etc.