• Journal of Positioning, Navigation, and Timing
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• v.10 no.3
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• pp.179-187
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• 2021

To estimate the location of the train, we consider an integrated navigation system that combines Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS). This system provides accurate navigation results in open sky by combining only the advantages of both systems. However, since measurement update cannot be performed in GNSS signal blocked areas such as tunnels, mountain, and urban areas, pure INS is used. The error of navigation information increases in this area. In order to reduce this problem, the train's Non-Holonomic Constraints (NHC) information can be used. Therefore, we deal with the INS/GNSS/NHC integrated navigation system in this paper. However, in the process of installing the navigation system on the train, a Mounting Misalignment Error of the IMU (MMEI) inevitably occurs. In this case, if the NHC is used without correcting the error, the navigation error becomes even larger. To solve this problem, a method of easily estimating the MMEI without an external device is introduced. The navigation filter is designed using the Extended Kalman Filter (EKF) by considering the MMEI. It is assumed that there is no vertical misalignment error, so only the horizontal misalignment error is considered. The performance of the integrated navigation system according to the presence or absence of the MMEI and the estimation performance of the MMEI according to the method of using NHC information are analyzed based on simulation. As a result, it is confirmed that the MMEI is accurately estimated by using the NHC information together with the GNSS information, and the performance and reliability of the integrated navigation system are improved.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.154-162
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• 2018

The multiplier circuit is necessary to estimate degradation status of electronic cards in nuclear power plant, but its accuracy is not easy in processing those functions to multiply two input signals. What is important in multiplier circuit is that the multiplication result must be accurate and its linearity must be perfect. We developed and proposed excellent linearity multiplier circuit using operational amplifiers and transistor characteristics, and then proved its validity in this paper. We have made efforts to eliminate nonlinearity components of semiconductors with this circuit in order to ensure excellent linearity of developed multiplier circuit. We conducted multiplication operations through simulation, applying adequate values to each component in order to verify the circuit composed of that method. We showed step-by-step output signals, and then compared the logical analyses and measuring results as simulation results. We confirmed that this method is superior to existing multiplication or linearity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.456-463
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• 2021

In this paper, Ultra Wide-Band(UWB) radar sensor is employed to detect flying drones and avoid collision in dense clutter environments. UWB signal is preferred when high resolution range measurement is required for moving targets. However, the time varying motion of flying drones may increase clutter noises in return signals and deteriorates the target detection performance, which lead to the performance degradation of anti-collision radars. We adopt a dynamic clutter suppression algorithm to estimate the time-varying distances to the moving drones with enhanced accuracy. A modified Constant False Alarm Rate(CFAR) is developed using an adaptive filter algorithm to suppress clutter while the false detection performance is well maintained. For this purpose, a velocity dependent CFAR algorithm is implemented to eliminate the clutter noise against dynamic target motions. Experiments are performed against flying drones having arbitrary trajectories to verify the performance improvement.

• Korean Journal of Optics and Photonics
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• v.31 no.6
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• pp.259-267
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• 2020

We evaluate the degradation of receiver sensitivity induced by direct and indirect exposure to solar irradiance in free-space optical communication systems. For this purpose, we calculate the variances of numerous noise components arising from solar irradiance, and then estimate the receiver sensitivity penalties for intensity-modulation/direct-detection and coherent systems. The results show that the penalties are less than 1.3 dB when indirect sunlight impinges on the detector, regardless of the system. However, the sensitivity penalties are estimated to be larger than 30 dB when the sunlight is directly incident upon the receiver. These penalties are barely reduced if we insert an optical polarizer, or if we adjust the bandwidth of an optical filter at the receiver to be as narrow as the signal's bandwidth.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1223-1230
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• 2021

Recently, energy resource management is a major concern around the world. Energy management activities minimize environmental impacts of the energy production. This paper presents design and prototyping of a home electric energy monitoring system that provides residential consumers with real time information about their electricity use. The developed system is composed of an in-house sensing system and a server system. The in-home sensing system is a set of wireless smart plug which have an AC power socket, a relay to switch the socket ON/OFF, a CT sensor to sense current of load appliance and a Kmote. The Kmote is a wireless communication interface based on TinyOS. Each sensing node sends its detection signal to a home gateway via wireless link. The home gateway stores the received signals into a remote database. The server system is composed of a database server and a web server, which provides web-based monitoring system to residential consumers. We analyzed and presented energy consumption data from electrical appliances for 3 months in home. The experimental results show the promising possibilities to estimate the energy consumption patterns and the current status.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.231-238
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• 2022

Mine detection has been mainly studied with images of the forward-looking sonar. Forward-looking sonar assumes the propagation path of the sound wave as a straight path, creating the surrounding images. This might lead to errors in the detection by ignoring the refraction of the sound wave. In this study, we propose a mine localization method that can robustly identify the location of mines in an underwater environment by considering the refraction of sound waves. We propose a method of estimating the elevation angle of arrival of the target echo signal in a single receiver, and estimate the mine location by applying the estimated elevation angle of arrival to ray tracing. As a result of simulation, the method proposed in this paper was more effective in estimating the mine localization than the existing method that assumed the propagation path as a straight line.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.410-418
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• 2022

Channel reliability estimation for iterative codes such as turbo codes is very important factor in time varying underwater acoustic channel, an incorrect estimation of channel reliability induced performance degradation. Therefore, this paper presents an optimal channel reliability estimation method for turbo coded FSK signal with rate of 1/3. The estimated BER algorithm is a method that can estimate the reliability of received data by comparing received data and decoded data, and we determine optimal channel reliability by using the method. In order to analyze the performance, the experiment was conducted on a lake in Munkyeong city by moving in the range of 300 m to 500 m. At the result of applying presented method to failed decoding packets, we confirm all packets are decoded successfully.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1469-1476
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• 2022

Recently, many researches have been conducted to estimate blood pressure using ECG(Electrocardiogram) and PPG(Photoplentysmography) signals. In this paper, we designed and implemented a mobile system to monitor blood pressure in real time by using 1-D convolutional neural networks. The proposed model consists of deep 11 layers which can learn to extract various features of ECG and PPG signals. The simulation results show that the more the number of convolutional kernels the learned neural network has, the more detailed characteristics of ECG and PPG signals resulted in better performance with reduced mean square error compared to linear regression model. With receiving measurement signals from wearable ECG and PPG sensor devices attached to the body, the developed system receives measurement data transmitted through Bluetooth communication from the devices, estimates systolic and diastolic blood pressure values using a learned model and displays its graph in real time.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1754-1759
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• 2022

The activity of gamma-ray emitting nuclides is calculated assuming that each gamma-ray is detected individually; thus, the magnitude of the coincidence summing signal must be considered during activity calculations. Here, the correction factor for the coincidence summing effect was calculated, and the detection efficiencies of two HPGe detectors were compared. The CANBERRA Inc. GC4018 high-purity Ge detector provided an estimate for the peak-to-total ratio using a point source to determine the coincidence summing correction factor. The ORTEC Inc. GEM60 high-purity Ge detector uses EFFTRAN in LVis to obtain the parameters of the detector and source model and the gamma-gamma and gamma-X match estimates, in order to determine the coincidence summing correction factor. Nuclide analyses, radioactivity comparisons, and analyses of reference material samples were performed utilizing certified reference materials to accurately determine the detection efficiencies. For both Co-60 and Y-88, the detection efficiency for a point source increased by an average of at least 12-13%, whereas the detection efficiency determined using LVis increased by an average of at least 13-15%. The calculated radioactivity values of the certified reference material and reference material samples were accurate to within 3% and 6% of the measured values, respectively.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.43-49
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• 2023

Object tracking is being studied with various techniques such as Kalman filter and Luenberger tracker. Even in situations, such as the one in which the system model is not well specified, to which existing signal processing techniques are not successfully applicable, it is possible to design artificial neural networks to track objects. In this paper, we propose an artificial neural network, which we call 'maximum-likelihood weighted-average neural network', to continuously track unpredictably moving objects. This neural network does not directly estimate the locations of an object but obtains location estimates by making weighted average combining various results of maximum likelihood tracking with different data lengths. We compare the performance of the proposed system with those of Kalman filter and maximum likelihood object trackers and show that the proposed scheme exhibits excellent performance well adapting the change of object moving characteristics.