• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.91-97
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• 2014

In this paper, we propose weighted detection probability with distance between primary user and secondary users by using cooperative spectrum sensing based on energy detection. And we analysis and simulate the result. We suggest different distance between primary user and secondary users and the wireless channel between primary user and secondary users is modeled as Gaussian channel. From the simulation results of the cooperative spectrum sensing with weighted method make coverage bigger compared with non-weight, and We show higher sensing efficiency when we put weight detection probability than before method.

• Journal of Advanced Navigation Technology
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• v.10 no.4
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• pp.377-384
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• 2006

In this paper the detection time of the distress signal for the satellite-based search and rescue (SAR) system is evaluated. Present LEOSAR system in operation employs a few Low-altitude Earth Orbit (LEO) satellites and hence provides poor and local coverage availability. This results in a considerably long waiting time for a distress beacon to be detected by a rescue mission control center. One can expect that the detection time of the distress signal will be significantly reduced if the proposed MEOSAR system, which is based on the Medium-altitude Earth Orbit (MEO) satellites, is implemented. Taking into account the influence of the obstacles on the beacon signal, simulations are carried out to evaluate the detection time of distress signals for the LEOSAR and MEOSAR systems and the corresponding results are analyzed.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.278-281
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• 2007

The purpose of this study is to develop snow and sea ice detection algorithm in Communication, Ocean and Meteorological Satellite (COMS) meteorological data processing system. Since COMS has only five channels, it is not affordable to use microwave or shortwave infrared data which are effective and generally used for snow detection. In order to estimate snow and sea ice coverage, combinations between available channel data(mostly visible and 3.7 ${\mu}m$) are applied to the algorithm based on threshold method. As a result, the COMS snow and sea ice detection algorithm shows reliable performance compared to MODIS products with channel limitation. Specifically, there is partial underestimation over the complicated vegetation area and overestimation over the area of high level clouds such as cirrus. Some corrections are performed by using water vapor and infrared channels to remove cloud contamination and by applying NDVI to detect more snow pixels for the underestimated area.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1670-1679
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• 2011

In the area of wireless sensor networks, sensor coverage and network connectivity problems are caused by a limited detection range and the communication distance of the nodes. To solve the coverage and connectivity problems, many studies are suggested, but most research is restricted to apply into the real environment because they didn't consider various environmental factors on wireless sensor network deployment. So in this paper, we propose a node deployment strategy considering environmental factors and the number of nodes in surveillance and reconnaissance sensor networks(SRSN). The proposed node deployment method divides the installation of the surveillance and reconnaissance sensor networks system into four steps such as identification of influences factors for node placement through IPB process, sensor node deployment based on sensing range, selection of monitoring site, and relay node deployment based on RF communication range. And it deploys the sensor nodes and relay nodes considered the features of the surveillance and reconnaissance sensor network system and environmental factors. The result of simulation indicates that the proposed node deployment method improves sensor coverage and network connectivity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.211-217
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• 2019

In an complicated battlefield environment, information from enemy's camp is an important factor in carrying out military operations. For obtaining this information, the number of UAVs that can be deployed to the mission without our forces' loss and at low cost is increasing. Because the mission environment has anti-aircraft weapons, mission space is needed for UAV to guarantee survivability without being killed. The concept of Configuration Space is used to define the mission space considering with range of weapons and detect range of UAV. UAV must visit whole given area to obtain the information and perform Coverage Path Planning for this. Based on threats to UAV and importance of information that will be obtained, area that UAV should visit first is defined. Grid Map is generated and mapping threat information to each grid for UAV path planning. On this study, coverage conditions and path planning procedures are presented based on the threat information on Grid Map, and mission space is expanded to improve detection efficiency. Finally, simulations are performed, and results are presented using the suggested UAV path planning method in this study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7A
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• pp.696-701
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• 2006

In this paper, we analyze the performance of double-dwell hybrid initial acquisition in DS-UWB system via detection, miss, false alarm probabilities and mean acquisition time. In the analysis, we consider the effect of the acquisition sequence, and deployment scenario of the abundant multipath components over the small coverage of the piconet in DS-UWB system. Based on the simulation, we obtain various performance on the mean acquisition time by varying the parameters, such as the total number of hypotheses to be searched, subgroup size, and dwell time. Then, we suggest the optimum parameter set for the initial acquisition in DS-UWB system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.994-1002
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• 2013

This study suggests a generalized availability and safety evaluation model to evaluate the influences to the system's fault tolerant capabilities depending on automatic fault detection function such as the automatic periodic testings. The conventional evaluation model of automatic fault detection function deals only with the self diagnostics, and supposes that the fault detection coverage of self diagnostics is always constant. But all of the fault detection methods could be degraded. For example, the periodic surveillance test has the potential human errors or test equipment errors, the self diagnostics has the potential degradation of built-in logics, and the automatic periodic testing has the potential degradation of automatic test facilities. The suggested evaluation models have incorporated the loss or erroneous behaviors of the automatic fault detection methods. The availability and the safety of each module of the safety grade platform have been evaluated as they were applied the automatic periodic test methodology and the fault tolerant evaluation models. The availability and safety of the safety grade platform were improved when applied the automatic periodic testing. Especially the fault tolerant capability of the processor module with a weak self-diagnostics and the process parameter input modules were dramatically improved compared to the conventional cases. In addition, as a result of the safety evaluation of the digital reactor protection system, the system safety of the digital parts was improved about 4 times compared to the conventional cases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.97-108
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• 2016

In this paper, we consider a cooperative monitoring network, which consists of a large number of UAVs, in order to promptly detect event in a disaster area. A command center may not be able to control each UAV individually due to resource constraints. Therefore, UAVs need to autonomously construct a mobile monitoring network in order to maximize monitoring coverage and to adapt the network formation according to environment changes in the disaster area. To that end, we propose multiple UAVs-based cooperative monitoring schemes that uses virtual forces. In this monitoring scheme, an effective monitoring is enabled by extending monitoring coverage using each UAV's circle movements. The UAVs-based monitoring network can also be splitted or merged in order to increase the monitoring effectiveness. Through simulations, we show that the proposed scheme can effectively monitor a large area and achieve a high event detection ratio.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.142-149
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• 2015

Most of the mono-camera based lane detection systems are fragile on poor illumination conditions. In order to compensate limitations of single sensor utilization, lane information fusion system using multiple lane sensors is an alternative to stabilize performance and guarantee high precision. However, conventional fusion schemes, which only concerns object detection, are inappropriate to apply to the lane information fusion. Even few studies considering lane information fusion have dealt with limited aids on back-up sensor or omitted cases of asynchronous multi-rate and coverage. In this paper, we propose a lane information fusion scheme utilizing multiple lane sensors with different coverage and cycle. The precise lane information fusion is achieved by the proposed fusion framework which considers individual ranging capability and processing time of diverse types of lane sensors. In addition, a novel lane estimation model is proposed to synchronize multi-rate sensors precisely by up-sampling spare lane information signals. Through quantitative vehicle-level experiments with around view monitoring system and frontal camera system, we demonstrate the robustness of the proposed lane fusion scheme.