• 경영과학
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• 제33권1호
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• pp.49-58
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• 2016

Focusing on the drastic increase of smart devices, machine generated data expansion is a general phenomenon in network services and IoT (Internet of Things). Especially, built-in multi sensors in a smart device are used for collection of user status and moving data. Combining the internal sensor data and environmental information, we can determine landmarks that decide a pedestrian's locations. We use an ANOVA method to analyze data acquired from multi sensors and propose a landmark classification algorithm. We expect that the proposed algorithm can achieve higher accuracy of indoor-outdoor positioning system for pedestrians.

• Journal of Communications and Networks
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• 제14권5호
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• pp.533-539
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• 2012

The performance analysis of wireless geolocation in a non-line-of-sight (NLOS) environment is a very important issue. Since Cramer-Rao lower bound (CRLB) determines the physical impossibility of the variance of an unbiased estimator being less than the bound, many studies presented the performance analysis in terms of CRLB. Several CRLBs for time-of-arrival (TOA), pseudo-range TOA, angle-of-arrival (AOA), and signal strength (SS) based positioning methods have been derived for NLOS environment. However, the performance analysis of time difference of arrival (TDOA) and TDOA/SS based geolocation techniques in a NLOS environment is still an opening issue. This paper derives the CRLBs of TDOA and TDOA/SS based positioning methods for NLOS environment. In addition, theoretical analysis proves that the derived CRLB for TDOA is the same as that of pseudo-range TOA and the TDOA/SS scheme has a lower CRLB than the TDOA (or SS) scheme.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 1999년도 추계학술대회논문집
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• pp.281-291
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• 1999

Productivity of container cranes and gantry cranes is influenced by the performance of crane hardware and cycle time. Cycle time in container handling is influenced by the path of containers and relative positioning of containers. So we have to minimize the sway of containers and spreaders to minimize relative positioning time. And sway minimization is influenced by the skill of workers in manual gantry cranes. In this paper, we will develop anti-sway system using mechanical and electrical method. Proposed hybrid system uses the basic structure of general manual gantry crane. So, it is very useful and effective. Electrical methods are main methods and mechanical methods are auxiliary methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.182-184
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• 2001

Linear pulse Motor(LPM) are used a field where smooth linear motion is required, and it's position accuracy higher than that of a lead. According to the advantage such as simplicity of mechanical frame, high reliability, precise open_loop operation, low inertia etc LPM is applied largely where it have made motor of this kind more and more attractive in many application areas such as factory automation and high speed positioning. This paper is researched to analyze for thrust force characteristic of hybrid LPM. Both the thrust and normal force are very sensitive to the airgap and tooth pitches of the force and platen. To find the optimal design parameter on the hybrid LPM for the embroidery machine. For the field analysis, the finite element method(FEM) is employed for calculating the force. The reluctance models will be used the magnetic permeance of airgap under static-conditions. The forces between forcer and platen have been calculated using the virtual work mathod.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부A
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• pp.37-39
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• 1998

The hybrid step motor has found applications in a wide range of mechanical systems as a low cost, open-loop positioning device. The step motor provides good stiffness at rest against disturbing load influences, a combination of moderate speed fine resolution, high reliability and simplicity. In recent years, considerable competition has arisen over the technological issue of wheather the device should be applied as a 2-Phase or 5-Phase machine. In this paper, to compare two systems, we have atempted to derive the mathematical. model, and analysed operating detent torque with this model. The analysis shows that a fundamental component of the permeance distribution produces the average torque and that harmonic components produce the ripple torque.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부A
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• pp.186-188
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• 1998

This paper describe the dynamic equation of Linear Pulse Motor(LPM)and the method of microstep drive and newly proposed control method for Linear Pulse Motor(LPM). A microstep drive is generally used for the high resolution positioning system. But high thrust distortion and imbalance in LPM make torque ripple that cause position error in microstep drive. In this paper the new control method is proposed and applied to hybrid LPM which is made by KERI. In the experimental results. it is shown the validity of the proposed control scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권12호
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• pp.3166-3181
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• 2012

Localization of mobile station (MS) has now gained considerable attention. Since the hybrid measurements can help to improve the positioning accuracy, several hybrid localization methods have been proposed in the literature. However, the high performance estimator with the closed-form solution and complete performance analysis for time-of-arrival/signal strength (TOA/SS) localization technique is still an opening issue. Two TOA/SS localization algorithms with the closed-form solutions are proposed for the cases with or without uncertainty in the positions of base stations. Furthermore, performance analysis for the TOA/SS localization technique is presented. Both the theoretical variances and Cramer-Rao lower bounds (CRLBs) are derived and the relationship between the cases with or without uncertainty is given. The paper also proves that the TOA/SS scheme has a lower CRLB than the TOA (or SS) scheme. Theoretical analysis and simulations show that the proposed method can reach its CRLB.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.1205-1207
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• 2015

Fingerprinting 방식에서 KNN은 WLAN 기반 실내 측위에 가장 많이 적용되고 있지만 KNN의 성능은 k개의 이웃 수와 RP의 수에 따라 민감하다. 논문에서는 KNN 성능을 향상시키기 위해 ANN 군집화를 적용한 KNN과 ANN을 혼합한 알고리즘을 제안하였다. 제안한 알고리즘은 신호잡음비 데이터를 KNN 방법에 적용하여 k개의 RP을 선택한 후 선택된 RP의 신호잡음비를 ANN에 적용하여 k개의 RP를 군집하여 분류한다. 실험 결과에서는 위치 오차가 2m 이내에서 KNN/ANN 알고리즘이 KNN 알고리즘보다 성능이 우수하다.

• 한국재난정보학회 논문집
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• 제17권4호
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• pp.802-816
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• 2021

연구목적: 본 논문에서는 개선된 특허 검색식을 제안하고 이에 기반 한 특허분석을 통해 Passive Tracking 기술분야의 잠재적 유망분야에 해당하는 공백기술을 도출하여 향후 수행해야 할 연구개발의 방향성을 제시한다. 연구방법: 본 논문에서는 기존의 검색식 구성 방식을 개선하여 유사어 DB, 최근 발표 논문의 Keyword, AI 검색 등의 다양한 Tool과 방법을 복합적으로 적용하는 기법을 제안하고, Passive Tracking 기술분야를 대상으로 광범위한 특허조사 및 분석을 통해, 기술 변화의 방향성 및 흐름을 확인하고, 해결하고자 하는 목적과 수단을 매트릭스화 하는 방법으로 공백기술을 도출한다. 연구결과: 제안하는 방법을 통해 Passive Tracking 기술분야 공백기술은 인공지능,적응형/복합형 측위기술 및 레이더/안테나를 활용한 '멀티 타깃 측위·추적기술'과 '3D 측위 기술'이 공백기술로 도출되었으며, 도출 결과의 타당성을 검토하기 위한 검색 결과 상용화 서비스 또는 제품이 부재함을 확인하였다. 결론: 본 논문에서 도출한 공백기술은 특허출원이 활발하지 않고 선점되어 있는 선행특허가 많지 않은 분야이므로, 보다 적극적인 연구개발과 특허출원 활동을 통해 기술에 대한 권리를 확보할 필요가 있다.

• 통합자연과학논문집
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• 제4권3호
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• pp.238-242
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• 2011

For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. The system that uses the artificial neural network(ANN) falls in a local minima when it learns many nonlinear data, and its classification accuracy ratio becomes low. To make up for this risk, the SVM/ANN hybrid algorithm is proposed in this paper. The proposed algorithm is the method that ANN learns selectively after clustering the SNR data by SVM, then more improved performance estimation can be obtained than using ANN only and The proposed algorithm can make the higher classification accuracy by decreasing the nonlinearity of the massive data during the training procedure. Experimental results indicate that the proposed SVM/ANN hybrid algorithm generally outperforms ANN algorithm.