• 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 the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.1009-1014
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• 2018

In this paper, we have designed and implemented a system that utilizes a radar sensor to measure distance between a sensor and objects. The sensor module creates raw data and uploads the data on the distance measuring system, which detects the presence of objects by using standard deviation and average filters. The experiment found that an algorithm using average filters measured people with error rates of up to 9.7 meters and a maximum error rate of 0.02 meters or less. While in an algorithm using standard deviations, it was found that an object is measured at an error rate of up to a maximum distance of 9.7 meters and a maximum error rate of 0.15 meters. Therefore, we have concluded that if a distance was measured by using a radar sensor, algorithms using average filters resulted in a higher accuracy than standard deviations filters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.448-458
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• 2020

Indoor positioning based on trilateration using common chord estimates location of a mobile subject by using intersection points between each circles which the radius is same as distance between the mobile subject and each radio-frequency transmitter. However, if the intersection points are not found due to error of the distance measurement, it causes failure of estimating the mobile subject's location. To prevent this case, numbers which is proportionate to radius of each circles, are temporarily added to each distances in order to lengthen radius of the circles. Although the estimated location includes error due to the radius extension, it is corrected again by the added value and distance from reference point. With introduction of the advanced correction algorithm, potential issues of existing trilateration such as failure of estimating location and distance measurement error will be minimized.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.9
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• pp.32-38
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• 2007

In this study, a new algorithm for measuring the velocity and distance from a camera to a moving object by using pseudo-stereo images obtained from a single camera with a stereo adapter is proposed. The proposed system is similar to a parallel visual stereo system using a two-camera system, but because this system can obtain pseudo-stereo images form a single camera, it has advantages not only in the aspect of cost but also in stereo conformity by arrangement and the calibration of the left and right stereo cameras upon image processing.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.1
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• pp.45-49
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• 2022

In this paper, we propose a method for estimating the error of the Ultra-Wideband (UWB) distance measurement using the channel impulse response (CIR) of the UWB signal based on machine learning. Due to the recent demand for indoor location-based services, wireless signal-based localization technologies are being studied, such as UWB, Wi-Fi, and Bluetooth. The constructive obstacles constituting the indoor environment make the distance measurement of UWB inaccurate, which lowers the indoor localization accuracy. Therefore, we apply machine learning to learn the characteristics of UWB signals and estimate the error of UWB distance measurements. In addition, the performance of the proposed algorithm is analyzed through experiments in an indoor environment composed of various walls.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.408-410
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• 2009

We present an efficient and robust measurement model for visual tracking. This approach builds on and extends work on subspace representations of measurement model. Subspace-based tracking algorithms have been introduced to visual tracking literature for a decade and show considerable tracking performance due to its robustness in matching. However the measures used in their measurement models are often restricted to few approaches. We propose a novel measure of object matching using Angle In Feature Space, which aims to improve the discriminability of matching in subspace. Therefore, our tracking algorithm can distinguish target from similar background clutters which often cause erroneous drift by conventional Distance From Feature Space measure. Experiments demonstrate the effectiveness of the proposed tracking algorithm under severe cluttered background.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.1
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• pp.25-30
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• 2014

In this paper, we have implemented an FMCW radar for a near distance measurement. In the structure of the FMCW radar, it is a key problem to solve the VCO nonlinearity. In this work, we have adopted a VCO nonlinearity compensation algorithm using the spectrum correlation of beat signals. The radar experimented in this work uses an X-band(9.55~10.25GHz) microwave signal, and realizes precision of 3% in the range of 30m. The prototype can be applied to the front surveillance radar such as in vehicle anti-collision and probing robot mission.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.127.6-127
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• 2001

In this paper, we deal with two bias compensation algorithms of acceleration sensor for measuring the galloping on power transmission line. Firstly, the block diagram of galloping measurement system is given and a galloping model is presented. Secondly, two compensation algorithms, a simple compensation and a period compensation, are proposed. A simple compensation algorithm use the drafts of velocity and distance at fixed periods, so it is useful for constant bias case. Next, a period compensation algorithm can compensate a periodic bias. This algorithm use the previous measured data and compensated data for constant period, where the period is obtained by FFT method. Lastly, the effectiveness of proposed algorithms is verified by comparing between two algorithms in simulation, and its characteristics and the bias error bound are shown, respectively.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.7
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• pp.914-920
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• 2003

In this paper, we deal with two drift compensation algorithms of acceleration sensor for measuring the galloping on power transmission line. Firstly, the block diagram of galloping measurement system is given and a galloping model is presented. Secondly, two compensation algorithms, a simple compensation and a period compensation, are proposed. A simple compensation algorithm uses the drifts of velocity and distance at fixed periods, so it is useful for constant drift case. Next, a period compensation algorithm can compensate a periodic drift. This algorithm uses the previous measured data and compensated data for constant period, where the period is obtained by FFT method. Lastly, the effectiveness of proposed algorithms is verified by comparing between two algorithms in simulation, and its characteristics and the drift error bound are shown, respectively.

• Journal of Radiation Protection and Research
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• v.28 no.1
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• pp.59-63
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• 2003

Purpose : Measurement of transmission dose is useful for in vivo dosimetry of QA purpose. The objective of this study is to develope an algorithm for estimation of tumor dose using measured transmission dose for open radiation field. Materials and Methods : Transmission dose was measured with various field size (FS), phantom thickness (Tp), and phantom chamber distance (PCD) with a acrylic phantom for 6 MV and 10 MV X-ray Source to chamber distance (SCD) was set to 150 cm. Measurement was conducted with a 0.6 cc Farmer type ion chamber. Using measured data and regression analysis, an algorithm was developed for estimation of expected reading of transmission dose. Accuracy of the algorithm was tested with flat solid phantom with various settings. Results : The algorithm consisted of quadratic function of log(A/P) (where A/P is area-perimeter ratio) and tertiary function of PCD. The algorithm could estimate dose with very high accuracy for open square field, with errors within ${\pm}0.5%$. For elongated radiation field, the errors were limited to ${\pm}1.0%$. Conclusion : The developed algorithm can accurately estimate the transmission dose in open radiation fields with various treatment settings.