• 한국기계가공학회지
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• 제15권2호
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• pp.89-96
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• 2016

Growing concerns regarding environmental pollution have increased the demand for green vehicles. Green vehicles include electric vehicles, compressed natural gas vehicles, fuel cell vehicles, and vehicles running on fuels such as bio diesel or an ethanol blend. CNG vehicles are equipped with a cylinder valve installed in a high-pressure vessel to control the CNG flow. For this purpose, the optimum design of cylinder valve solenoid is necessary to secure at driving a CNG vehicle. In this study, electromagnetic field analysis to ensure the reliable operation of the solenoid was conducted by using a Maxwell V15. The electromagnetic field analysis was performed by magnetostatic technique according to distance between magnetic poles in order to predict the attraction force. Finally, the attraction force was validated through comparison between the Maxwell results and the measurement results. From the results, the error of attraction force was found to be 2.85 N to 6.5 N under the testing conditions.

• 한국컴퓨터정보학회논문지
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• 제13권7호
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• pp.67-73
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• 2008

본 논문에서는 무선 센서 노드의 실내 위치 추적 시스템을 제안한다. 위치 추정에 사용하는 센서 값으로 RF 인터페이스의 수신 신호 강도 (RSSI)를 사용한다. 이동 노드를 부착한 사용자와 실내에 고정된 다수의 고정 노드의 신호 강도를 수신하여 사용자의 위치를 결정한다. 제안한 시스템은 측정에 의한 2.4GHz log-normal path loss 모델의 수신강도와 유클리드 거리 계산 방법과 신호 강도를 결합한다. 실험결과를 통해서 1.3m 이내의 오차로 위치를 추정함을 확인하였다.

• 한국음향학회지
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• 제20권1호
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• pp.62-67
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• 2001

직선집속 PVDF 초음파 트랜스듀서를 이용하여 누설탄성표면파 (Leaky Surface Acoustic Wave: LSAW)의 전파속도를 측정하고, 그 결과를 이론해석 결과와 비교하였다. 시료로는 등방성 재료인 구리, 알루미늄 및 용융석영, 이방성 재료인 Z-cut α/sup-/수정을 사용하였다. 측정방법으로는 초점면에 위치한 시료를 트랜스듀서 쪽으로 접근시켰을 때 LSAW가 트랜스듀서의 중심축을 통과한 후 시료표면에서 직접 반사되어오는 종파와 분리되어지는 현상을 이용하였다. 음속의 측정결과는 이론 해석결과와 오차 1％이내에서 잘 일치하였으며,α/sup-/수정의 (0,0,1)면에서는 LSAW 외에 의사누설탄성표면파 (Leaky Pseudo Surface Acoustic Wave : LPSAW)가 전형적인 6-fold 이방성을 가지고 전파됨을 알 수 있었다.

• 한국통신학회논문지
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• 제39B권9호
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• pp.570-577
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• 2014

거리 기반 실시간 측위 시스템에서 보다 정확한 측위가 가능하기 위해서는 우수한 측위 알고리즘과 함께 거리측정의 정확도 확보도 필수적으로 요구된다. 본 논문에서는 두 노드 간의 실제적인 거리측정의 정확도를 평가하기 위해 기존의 Symmetry 가정이 제거된 SDS-TWR 거리계산식 유도에 의한 정성적인 분석을 수행하고, 개발된 센서노드를 활용해 테스트 네트워크를 구축한 후 실험결과에 의한 정량적인 평가를 동시에 수행한다. 본 연구에서 구현된 IEEE 802.15.4a 소프트웨어 스택을 탑재한 센서노드 환경이 기존 나노트론사의 상용 참조보드 환경보다 평균 약 60% 감소된 거리측정 오차율을 산출하여 상대적으로 매우 높은 거리측정 정확도를 보인다.

• 한국지능시스템학회논문지
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• 제21권3호
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• pp.296-301
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• 2011

본 논문에서는 군집 로봇의 동시적 위치 추정 및 지도 작성 시스템을 제안하였다. 로봇은 실험환경에서 주변 환경을 인식하기 위해 초음파센서와 비젼 센서를 이용하였다. 실험환경을 3개의 영역으로 분할하였고, 로봇은 각 영역에서 초음파 센서로 주변 환경에 대한 거리 정보를 측정하였고, SURF 알고리즘을 이용하여 비젼 센서로부터 입력받은 영상과 landmark의 특징점을 정합하여 랜드마크를 인식하였다. 제안된 방법은 센서값들에 대한 오차에 민감하지 않고 실험환경에 비교적 정확한 지도를 작성함으로써 응용 가능성을 증명하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.721-724
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• 2014

초음파센서는 저렴성, 단순한 구조, 기계적 강인성, 사용상의 적은 제약 등의 이점 때문에 다양한 응용분야에 적용된다. 물체의 인식에 초음파센서를 사용하기에는 낮은 분해능을 초래하는 불량한 방향성과 측정오류를 유발하는 반사성의 어려움을 내재하고 있다. 이런 문제를 개선하기 위해서 다양한 센서의 배열형태에서 많은 수의 센서를 사용하거나, 일정 수의 센서를 사용할 경우에는 센서의 배열을 기계적으로 이동시킨다. 본 논문에서는 물체의 패턴인식에 있어서 가장 기본적인 거리, 물체크기, 물체각도 값을 얻기 위해 간단하게 구성된 전자회로를 부가하여 초음파센서의 송출전압을 여러 단계로 변경시켜 얻어낸 데이터에 뉴로퍼지 기반의 지능적 계산 알고리즘을 적용하여 개선된 결과를 얻는다.

• International Journal of Internet, Broadcasting and Communication
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• 제13권1호
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• pp.161-167
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• 2021

This paper proposes a new personalized HRTF estimation method which is based on a deep neural network (DNN) model and improved elevation reproduction using a notch filter. In the previous study, a DNN model was proposed that estimates the magnitude of HRTF by using anthropometric measurements [1]. However, since this method uses zero-phase without estimating the phase, it causes the internalization (i.e., the inside-the-head localization) of sound when listening the spatial sound. We devise a method to estimate both the magnitude and phase of HRTF based on the DNN model. Personalized HRIR was estimated using the anthropometric measurements including detailed data of the head, torso, shoulders and ears as inputs for the DNN model. After that, the estimated HRIR was filtered with an appropriate notch filter to improve elevation reproduction. In order to evaluate the performance, both of the objective and subjective evaluations are conducted. For the objective evaluation, the root mean square error (RMSE) and the log spectral distance (LSD) between the reference HRTF and the estimated HRTF are measured. For subjective evaluation, the MUSHRA test and preference test are conducted. As a result, the proposed method can make listeners experience more immersive audio than the previous methods.

• Journal of Positioning, Navigation, and Timing
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• 제11권3호
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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.

• Journal of Positioning, Navigation, and Timing
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• 제13권1호
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• pp.103-110
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• 2024

In this paper, a test bed for real-time network Real-Time Kinematic (RTK) research was constructed using reference stations of the NGII. A group of candidate station networks was derived, including three stations in Seoul. The group consisted of four stations with a distance of less than 100 km between them. Among several candidates, a network composed of stations with short distances between them and demonstrating good data quality for all reference stations was selected as the test bed. After collecting real-time data in Radio Technical Committee for Maritime services (RTCM) format from the selected stations and conducting a noise analysis on measurements, mm-level carrier phase measurement noise was confirmed. Afterwards, the user set the reference station inside the test bed and analyzed the network RTK positioning performance of the MAC method using the GPS L1 frequency as post-processing. From the result of the analysis it was confirmed that the residual error for all users was within 10 cm after applying the correction. Additionally, after determining integer ambiguities through Least-squares AMBiguity Decorrelation Adjustment (LAMBDA), it was confirmed that the fix rate was 100%, and all ambiguities were resolved as true values.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권4호
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• pp.173-180
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• 2006

A key component of autonomous navigation of intelligent home robot is localization and map building with recognized features from the environment. To validate this, accurate measurement of relative location between robot and features is essential. In this paper, we proposed relative localization algorithm based on 3D reconstruction of scale invariant features of two images which are captured from two parallel cameras. We captured two images from parallel cameras which are attached in front of robot and detect scale invariant features in each image using SIFT(scale invariant feature transform). Then, we performed matching for the two image's feature points and got the relative location using 3D reconstruction for the matched points. Stereo camera needs high precision of two camera's extrinsic and matching pixels in two camera image. Because we used two cameras which are different from stereo camera and scale invariant feature point and it's easy to setup the extrinsic parameter. Furthermore, 3D reconstruction does not need any other sensor. And the results can be simultaneously used by obstacle avoidance, map building and localization. We set 20cm the distance between two camera and capture the 3frames per second. The experimental results show :t6cm maximum error in the range of less than 2m and ${\pm}15cm$ maximum error in the range of between 2m and 4m.