• Annual Conference of KIPS
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• 2021.05a
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• pp.263-266
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• 2021

근래의 드론 산업은 다양한 분야에서 사용이 확대되고 있으나 규제 등 여러 가지 사회적 진입장벽으로 시장 진입에 애로사항이 도출되고 있다. 본 논문에서는 드론 산업의 여러 제약 중 배터리의 제한적인 용량으로 장시간 비행이 어려운 문제를 개선하고자 승강식 드론스테이션을 개발하였다. 승강식 드론스테이션은 드론의 비행 중 배터리가 방전될 시 충전 및 정비를 할 수 있고, 드론 간의 통신 중계기 역할을 수행한다. 본 논문에서는 스테이션에 드론이 접근 시 슬라이딩 도어를 개폐하기 위하여 초광대역 통신을 이용한 거리 측정과 위치 인식 시스템에 대한 내용을 기술하였다.

• Current Optics and Photonics
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• v.8 no.2
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• pp.127-137
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• 2024

The distribution of tags is an important factor that affects the performance of radio-frequency identification (RFID). To study RFID performance, it is necessary to obtain RFID tags' coordinates. However, the positioning method of RFID technology has large errors, and is easily affected by the environment. Therefore, a new method using optical measurement is proposed to achieve RFID performance analysis. First, due to the possibility of blurring during image acquisition, the paper derives a new image prior to removing blurring. A nonlocal means-based method for image deconvolution is proposed. Experimental results show that the PSNR and SSIM indicators of our algorithm are better than those of a learning deep convolutional neural network and fast total variation. Second, an RFID dynamic testing system based on photoelectric sensing technology is designed. The reading distance of RFID and the three-dimensional coordinates of the tags are obtained. Finally, deep learning is used to model the RFID reading distance and tag distribution. The error is 3.02%, which is better than other algorithms such as a particle-swarm optimization back-propagation neural network, an extreme learning machine, and a deep neural network. The paper proposes the use of optical methods to measure and collect RFID data, and to analyze and predict RFID performance. This provides a new method for testing RFID performance.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1733-1737
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• 2024

In order to specify the location of the scintillation pixel that interacted with gamma rays in the positron emission tomography (PET) detector, conventionally, after acquiring a flood image, the location of interaction between the scintillation pixel and gamma ray could be specified through a pixel-segmentation process. In this study, the experimentally acquired signal was specified as the location of the scintillation pixel directly, without any conversion process, through the simulation data and the deep learning algorithm. To evaluate the accuracy of the specification of the scintillation pixel location through deep learning, a comparative analysis with experimental data through pixel segmentation was performed. In the same way as in the experiment, a detector was configured on the simulation, a model was built using the acquired data through deep learning, and the location was specified by applying the experimental data to the built model. Accuracy was calculated through comparative analysis between the specified location and the location obtained through the segmentation process. As a result, it showed excellent accuracy of about 85 %. When this method is applied to a PET detector, the position of the scintillation pixel of the detector can be specified simply and conveniently, without additional work.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.228-235
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• 2007

The main purpose of this paper is to manage the container property effectively at the container yard by applying the RTLS technology to the field of port logistics. Yet, many kinds of noises happen to be inputted with the distance value(between the reader and the tag) which is to be inputted into the location identification algorithm, which makes the distance value jumped due to the system noise of the ultrasonic sensor module and the measurement noise. The Kalman Filter is widely used to prevent this jump occurrence; the noises are eliminated by using the EKF(Extended Kalman Filter) while considering that the distance information of the ultrasonic sensor is non-linear. Also, the 3D RTLS system at the port container yard suggested in this research is designed not to be interrupted for its ultrasonic transmission by positioning the antenna at the front of each sector of the container where the active tags are installed. We positioned the readers, which function as antennas for location identification, to four places randomly in the absolute coordinate and let the positions of the active tags identified by using the distance data delivered from the active tags. For the location identification algorithm used in this paper, the triangulation measurement that is most used in general is applied and newly reorganized to calculate the position of the container. In the first experiment, we dealt with the error resulting in the angle and the distance of the ultrasonic sensor module, which is the most important in the hardware performance; in the second, we evaluated the performance of the location identification algorithm, which is the most important in the software performance, and tested the noise cancellation effects for the EKF. According to the experiment result, the ultrasonic sensor showed an average of 3 to 5cm error up to $45^{\circ}$ in case of $60^{\circ}$ or more, non-reliable linear distances were obtained. In addition, the evaluation of the algorithm performance showed an average of $4^{\circ}{\sim}5^{\circ}$ error due to the error of the linear distance-this error is negligible for most container location identifications. Lastly, the experiment results of noise cancellation and jump preservation by using the EKF showed that noises were removed in the distance information which was entered from the input of the ultrasonic sensor and as a result, only signal was extracted; thus, jumps were able to be removed and the exact distance information between the ultrasonic sensors could be obtained.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.647-654
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• 2016

Indoor localization based on visible-light communication using the received signal strength intensity (RSSI) has been widely studied because of its high accuracy compared with other wireless localization methods. However, because the RSSI can vary according to the inclination and azimuth of the receiver, a large error can occur, even at the same position. In this paper, we propose a visible-light communication-based 3-D indoor positioning algorithm using the Gauss-Newton technique in order to reduce the errors caused by the change in the inclination of the receiver. The proposed system reduces the amount of computations by selecting the initial position of the receiver through the linear least-squares method (LSM), which is applied to the RSSIs, and improves the position accuracy by applying the Gauss-Newton technique to the 3-D nonlinear model that contains the RSSIs acquired by the changes in the azimuth and inclination of the receiver. In order to verify the validity of the proposed algorithm in an indoor space with dimensions of $6{\times}6{\times}3m$ where 16 LED lights are installed, we compare and analyze the errors of the conventional linear LSM-based trilateration technique and the proposed algorithm according to the changes in the inclination and azimuth of the receiver. The experimental results show that the location accuracy of the proposed algorithm is improved by 82.5% compared to the conventional LSM-based trilateration technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.1-8
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• 2016

In this study, an WiFi fingerprinting method based on the k-nn algorithm was applied to improve the accuracy of location tracking of a moving train on a platform and evaluate the performance to minimize the estimation error of location tracking. The data related to the position of the moving train are monitored by the control center for trains and used widely for the safety and comfort of passengers. The train location tracking methods based on WiFi installed by telecom companies were evaluated. In this study, a simulator was developed to consider the environments of two cases; in already installed WiFi devices and new installed WiFi devices. The developed simulator can simulate the localized estimation of the position under a variety of conditions, such as the number of WiFi devices, the area of platform and entry velocity of train. To apply location tracking algorithms, a k-nn algorithm and fuzzy k-nn algorithm were applied selectively according to the underlying condition and also four distance measurement algorithms were applied to compare the error of location tracking. In conclusion, the best method to estimate train location tracking is a combination of the k-nn algorithm and Minkoski distance measurement at a 0.5m grid unit and 8 WiFi AP installed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.225-232
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• 2013

In this paper, we introduce a method that can be used to select the position of head node for context-awareness information. The validity of the head node optimal location is saving the energy in the path according to the clustering. It is important how to elect one of the relay node for energy efficiency routing. Existing LEACH algorithm to elect the head node when the node's energy probability distribution function based on the management of the head node is optional cycle. However, in this case, the distance of the relay node status information including context-awareness parameters does not reflect. These factors are not suitable for the relay node or nodes are included in the probability distribution during the head node selects occurs. In particular, to solve the problems from the LEACH-based hierarchical clustering algorithms, this study defines location with the status context information and the residual energy factor in choosing topology of the structure adjacent nodes. The proposed ECOPS (Energy Conserving Optimal path Schedule) algorithm that contextual information is contributed for head node selection in topology protocols. This proposed algorithm has the head node replacement situations from the candidate head node in the optimal path and efficient energy conservation that is the path of the member nodes. The new head node election technique show improving the entire node lifetime and network in management the network from simulation results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.49-59
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• 2011

Recently, ToA and TDoA estimation are favorable among all of estimation techniques because they have the best accuracy in estimating position. ToA and TDoA estimation are typical techniques based on time. So, it is important to have the time syncronization and offset between a target node and several reference nodes. If they don't have the time syncronization between a reference node and target node or have a time offset among reference nodes, the positioning error will increase due to the ranging error. The conventional positioning algorithm does not have a accurate device's position because ranging error is added the calc dation of the position. In this paper, we propose a hybrid method of ToA and TDoA ll increase due. We use MHP pulse that has orthogonal pulse instead of the existing pulse to transmit and receive pulses between a target node and reference nodes. We can estimate the target node's position by ToA and TDoA estimation to transmit and receive MHP pulses only once. When the proposed Hybrid method iteratively calculate the distance, we can select the ranging technique to have more accurate position. The simulation results confirm the enhancement of the Hybrid method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.375-384
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• 2013

Most of regions within the city of Mokpo, located on the southwest coast of the Korean Peninsula, are subjected to significant subsidence because about 70% of the city is land reclaimed from the sea (Kim et al., 2005). In this study, we aimed to estimate the rate of subsidence over Mokpo by using PALSAR L-band dataset from 2006 to 2010. Time series analysis was performed as well using GPS surveying data from 2010 to 2012. Results from these two independent datasets are then compared and analyzed over the common period of time. GPS data processing provides the results of seasonal variation on the surface, that is, via repeatedly rising and falling in association with the periodic cycle. Therefore, a time series analysis was performed to calculate the rate of ground subsidence. The deformation rates calculated for the same point are 3.89cm/yr and 2.65cm/yr from the GPS data and SAR data, respectively. SAR and GPS data processing results show a very similar pattern in terms of magnitude of annual subsidence. Thus, if the two datasets are integrated together, new modeling on ground subsidence is feasible. Lastly, subsidence was detected in a landfill area in the city of Mokpo, which has been continuously occurring through 2012.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.76-85
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• 2009

UWB signal with high resolution capability can be used to estimate ranging and positioning in wireless personal area network. The node works on its local clock and the frequency differences of nodes have serious affects on ranging algorithms estimating locations of mobile nodes. The low rate UWB, IEEE802.15.4a, describes asynchronous two way ranging methods such as TWR and SDS-TWR working without any additional network synchronization, but the algorithms can not eliminate the effect of clock frequency differences. Therefore, the mechanisms to characterize the crystal difference is essential in typical UWB PHY implementations. In high rate UWB, characterizing of crystal offset with tracking loop is not required. But, detection of the clock frequency offset between the local clock and remote clock can be performed if there is little noise induced jitter. In this paper, we complete related ranging equations of high rate UWB based on TWR with relative frequency offset, and analyze a residual error in the ideal equations. We also evaluate the performance of the relative frequency offset algorithm by simulation and analyze the ranging errors according to the number of TWR to compensate coarse clock resolution. The results show that the relative frequency offset compensation and many times of TWR enhance the performance to converge to a limited ranging errors even with coarse clock resolutions.