• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.61-67
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• 2021

With the recent development of bathemetry technology, the hydrographic surveying method has been changed from single beam depth device use to multi beam acoustic sounding technology. Also, various studies have been reported to obtain high accuracy and precision in the process of river bed topographic data. Especially south korea is geographically on three sides of the sea and the river topography is very developed. To build information about the underwater, and riverbed status, the public investigations has been continuously progressed. In this study, We investigasted the riverbed topography near Baeckma river leisure park. for this purpose, In this study, as the first preliminary survey, location of navigational dangerous objects and reefs and the dangerous areas are identified. Also, ground control points is selected for the optimal GPS surveying. Secondary, through test surveying the Gain, TVG, and pulse length are determined. In addition, the investigation of dangerous objects for navigation is also conducted. As the last step, the error analysis are conducted for the acquired data, and this process involves the removal and adjustments of errors. This section includes the analysis of tide level and navigational contributions, and finally generates a submarine topographic map.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.676-683
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• 2021

Wi-Fi Round-trip timing (RTT) based location estimation technology estimates the distance between the user and the AP based on the transmission and reception time of the signal. This is because reception instability and signal distortion are greater than that of a Received Signal Strength Indicator (RSSI) based fingerprint in an indoor NLOS environment, resulting in a large position error due to multipath fading. To solve this problem, in this paper, we propose an end-to-end based WiFi Trilateration Net (WTN) that combines neural network-based RTT correction and trilateral positioning network, respectively. The proposed WTN is composed of an RNN-based correction network to improve the RTT distance accuracy and a neural network-based trilateral positioning network for real-time positioning implemented in an end-to-end structure. The proposed network improves learning efficiency by changing the trilateral positioning algorithm, which cannot be learned through differentiation due to mathematical operations, to a neural network. In addition, in order to increase the stability of the TOA based RTT, a correction network is applied in the scanning step to collect reliable distance estimation values from each RTT AP.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.2
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• pp.187-196
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• 2021

The Network-Centric warfare over weapon data link networks has been developed for the recent decade. Since the US navy had begun to develop tactical digital information chain, it has gradually transformed into weapon data link technology. As data link network system and its protocol have been advanced into high-technology, focusing and targeting on moving targets become possible in net-enabled environments. However, it is difficult to identify the primary information from numerous battlefields and understanding approaches to damage a target in a timely manner. In this paper, to better understand the targeting assessment, we suggest a specific solution: Bomb Hit Indication(BHI) using information in weapon data link messages. In order to prove our suggestion, we implement the BHI solution and apply it into the weapon data link integrating system.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2941-2959
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• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.199-208
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• 2022

Inertial Navigation System (INS)/Global Navigation Satellite System (GNSS) integrated navigation system can be used for land vehicle navigation. When the GNSS signal is blocked in a dense urban area or tunnel, however, the problem of increasing the error over time is unavoidable because navigation must be performed only with the INS. In this paper, Non-Holonomic Constraints (NHC) information is utilized to solve this problem. The NHC may correct some of the errors of the INS. However, it should be noted that NHC information is not applicable to all areas within the vehicle. In other words, the lever arm effect occurs according to the distance between the Inertial Measurement Unit (IMU) mounting position and the NHC effective point, which causes the NHC condition not to be satisfied at the IMU mounting position. In this paper, an INS/GNSS/NHC integrated navigation filter is designed, and this filter has a function to compensate for the lever arm effect. Therefore, NHC information can be safely used regardless of the vehicle's driving environment. The performance of the proposed technology is verified through Monte-Carlo simulation, and the performance is confirmed through experimental test.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.8-13
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• 2023

We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.

• Annual Conference of KIPS
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• 2009.04a
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• pp.1178-1181
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• 2009

Geographic forwarding algorithms을 사용하는 Georouting protocol에서는 route maintenance을 위해서 고정된 주기마다 beacon message을 이웃노드에 전송하는 fixed periodical beacon based route algorithm을 사용하여 mobile node 정보를 습득한다. Fixed periodical beacon scheme에서의 기존 연구 이슈는 이웃노드 정보의 신뢰성을 유지하기 위해서 다양한 mobility environment 환경에 맞도록 beacon 전송주기를 적절히 결정하는 연구가 진행되어 왔다. 이와 같은 연구에서는 long periodical interval 사용 시 이웃노드의 위치정보 error을 발생시킬 확률이 높으며 또한 short periodical interval 의 경우 네트워크 내에 high route overhead 을 유발시키는 단점을 가지고 있다. 따라서 고정된 주기 방법은 다양한 mobility environment에 잘 적용되지 못하며 또한 mobility environment 에서 발생하는 route maintenance 내에 이웃노드 정보에 대한 불확실성 문제가 빈번이 발생하여 경로 설정에 잘못된 정보를 제공하여 경로 신뢰성(path reliability)과 낮은 전송률 (transmission rate)을 야기한다. 본 논문에서는 이런 이웃노드 정보의 불확실성 문제를 극복하기 위해서 mobile node가 스스로 자신의 위치를 체크하여 routing table을 능동적으로 갱신하는 방법을 이용하여 이 문제를 극복할 수 있도록 하였다. 모의 실험은 ns2를 이용하여 실시하였으며 결과는 low/high mobility scenario에서는 기존 방법 보다 routing overhead 을 줄이면서 높은 전송률 (transmission rate)을 보인다.

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• Progress in Superconductivity and Cryogenics
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• v.9 no.3
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• pp.13-15
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• 2007

We employed home-made position marking module in the scanning Hall probe system. The module is composed of two coils of which gap, a, between wires in a coil is $500{\mu}m$. We appiled 10-35mA of current with 15Hz in the coils and recorded ac corresponding magnetic field signal with respect to measuring time while we measured DC field profiles produced due to superconducting film in a perpendicular magnetic field. We calibrate the position, x, of coils using the measuring time and location of the coils in the holder. The error range was about ${\pm}0.1mm$. We test the module as we applied current of 100A and filed of 1kG in the superconducting tape. It was confirmed that there was no interference between superconducting tape and marking coils.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.92-100
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• 2023

Wireless communication technology is becoming increasingly prevalent in smart factories, but the rise in the number of wireless devices can lead to interference in the ISM band and obstacles like metal blocks within the factory can weaken communication signals, creating radio shadow areas that impede information exchange. Consequently, accurately determining the radio communication coverage range is crucial. To address this issue, a Radio Environment Map (REM) can be used to provide information about the radio environment in a specific area. In this paper, a technique for estimating an indoor REM usinga mobile robot and machine learning methods is introduced. The mobile robot first collects and processes data, including the Received Signal Strength Indicator (RSSI) and location estimation. This data is then used to implement the REM through machine learning regression algorithms such as Extra Tree Regressor, Random Forest Regressor, and Decision Tree Regressor. Furthermore, the numerical and visual performance of REM for each model can be assessed in terms of R2 and Root Mean Square Error (RMSE).