• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1401-1410
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• 2014

This paper presents a modified adaptive fading EKF (AFEKF) for sensor fault detection and isolation in the satellite. Also, the fault detection and isolation (FDI) scheme is developed in three phases. In the first phase, the AFEKF is modified to increase sensor fault detection performance. The sensor fault detection and sensor selection method are proposed. In the second phase, the IMM filer with scalar penalty is designed to detect wherever actuator faults occur. In the third phase of the FDI scheme, the sub-IMM filter is designed to identify the fault type which is either the total or partial fault. An important feature of the proposed FDI scheme can decrease the number of filters for detecting sensor fault. Also, the proposed scheme can classify fault detection and isolation as well as fault type identification.

• 한국통신학회논문지
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• 제39C권10호
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• pp.909-919
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• 2014

License plate (LP) detection is the most imperative part of an automatic LP recognition (LPR) system. Typical LPR contains two steps, namely LP detection (LPD) and character recognition. In this paper, we propose an efficient Vehicle-to-LP detection framework which combines with an adaptive GMM (Gaussian Mixture Model) and a cascade of boosted classifiers to make a faster vehicle LP detector. To develop a background model by using a GMM is possible in the circumstance of a fixed camera and extracts the motions using background subtraction. Firstly, an adaptive GMM is used to find the region of interest (ROI) on which motion detectors are running to detect the vehicle area as blobs ROIs. Secondly, a cascade of boosted classifiers is executed on the blobs ROIs to detect a LP. The experimental results on our test video with the resolution of $720{\times}576$ show that the LPD rate of the proposed system is 99.14% and the average computational time is approximately 42ms.

• 한국멀티미디어학회논문지
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• 제16권12호
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• pp.1368-1375
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• 2013

본 논문에서는 공간 적응적인 노이즈 검출 및 제거 방식에 대해 제안한다. 관측 영상 및 첨가 노이즈가 가우시안 분포 특성을 갖고 있다는 가정 하에 국부 통계 특성을 이용하여 노이즈 매개 변수들을 예측하며, 예측된 매개변수들은 1차 마르코프 랜덤 장과 연동하여 노이즈 검출 과정의 제약 조건을 설정하기 위해 사용된다. 더불어, 노이즈 검출 과정에서 설정된 제약 조건에 따라 제안된 가변 크기의 적응 저주파 통과 필터를 사용하여 적응적으로 복원 영상의 완화 정도를 제어하였다. 실험 결과를 통해 제안 방식의 효율성을 입증할 수 있었다.

• 대한전자공학회논문지SP
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• 제41권6호
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• pp.99-108
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• 2004

본 논문에서는 CCD(charge-coupled device) 영상 기반의 자동 표적 탐지 시스템(ATD System : Automatic Target Detection System)에 적합한 빠른 탐색 방법을 제안한다. 무기체계에서의 활용을 위해서는 빠른 연산이 주요한 변수인 만큼 이 논문에서는 적은 계산량으로 다양한 표적을 탐지할 수 있는 능력에 주안점을 두고 있다. 표적 훈련(train)단계에서는 구간별 수직 방향 프로젝션을 이용하여 1D의 템플릿을 구성하고 K-means clustering과 이진 트리 구조(binary tree structure)를 활용하여 실제 시험 단계에서 템플릿 정합하는 횟수를 최소화한다. 또한 Correlation-based Adaptive Predictive Search(CAPS)를 이용하여 각각의 템플릿에 적응적인 skip-width를 사용하여 탐색 속도를 높이고 클러터 제거 단계에서는 윤곽선으로부터 추출한 Fourier Descriptor계수를 비교함으로써 초기 탐지에서 타겟으로 오인된 클러터를 모양 정보에 기반해서 제거하는 방법을 사용한다.

• 제어로봇시스템학회논문지
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• 제21권3호
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• pp.283-289
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• 2015

In this paper, a GNSS interference detection algorithm based on an adaptive fading Kalman filter is proposed to detect a spoofing signal which is one of the threatening GNSS intentional interferences. To detect and mitigate the spoofing signal, the fading factor of the filter is used as a detection parameter. For simulation, the effect of the spoofing signal is modeled by the ramp type bias error of the pseudorange to emulate a smart spoofer and the change of the fading factor value according to ramp type bias error is quantitatively analyzed. In addition, the detection threshold is established to detect the spoofing signal by analyzing the change of the error covariance and the effect of spoofing is mitigated by controlling the Kalman gain of the filter. To verify the performance analysis of the proposed algorithm, various simulations are implemented. Through the results of simulations, we confirmed that the proposed algorithm works well.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.2080-2085
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• 2018

There have been numerous studies that extract the R-peak from electrocardiogram (ECG) signals. All of these studies can extract R-peak from ECG. However, these methods are complicated and difficult to implement in a real-time portable ECG device. After filtration choosing a threshold value for R-peak detection is a big challenge. Fixed threshold scheme is sometimes unable to detect low R-peak value and adaptive threshold sometime detect wrong R-peak for more adaptation. In this paper, a simple and robustness algorithm is proposed to detect R-peak with less complexity. This method also solves the problem of threshold value selection. Using the adaptive filter, the baseline drift can be removed from ECG signal. After filtration, an appropriate threshold value is automatically chosen by using the minimum and maximum value of an ECG signals. Then the neighborhood searching scheme is applied under threshold value to detect R-peak from ECG signals. Proposed method improves the detection and accuracy rate of R-peak detection. After R-peak detection, we calculate heart rate to know the heart condition.

• Journal of Communications and Networks
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• 제5권1호
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• pp.33-42
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• 2003

In this paper a two-stage maximum-likelihood (ML) detection structure for group detection in DS/CDMA systems is presented. The first stage of the receiver is a linear filter, aimed at suppressing the effect of the unwanted (i.e., out-of-grout) users' signals, while the second stage is a non-linear block, implementing a ML detection rule on the set of desired users signals. As to the linear stage, we consider both the decorrelating and the minimum mean square error approaches. Interestingly, the proposed detection structure turns out to be a generalization of Varanasi's group detector, to which it reduces when the system is synchronous, the signatures are linerly independent and the first stage of the receiver is a decorrelator. The issue of blind adaptive receiver implementation is also considered, and implementations of the proposed receiver based on the LMS algorithm, the RLS algorithm and subspace-tracking algorithms are presented. These adaptive receivers do not rely on any knowledge on the out-of group users' signals, and are thus particularly suited for rejection of out-of-cell interference in the base station. Simulation results confirm that the proposed structure achieves very satisfactory performance in comparison with previously derived receivers, as well as that the proposed blind adaptive algorithms achieve satisfactory performance.

• 한국통신학회논문지
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• 제38B권9호
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• pp.736-743
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• 2013

적외선 탐색 및 추적 시스템에서 원거리에 표적이 존재할 경우 표적의 크기가 매우 작고, 해무와 같은 클러터와 다양한 센서 잡음으로 인해 표적의 검출이 매우 어렵다. 특히 표적의 화소 값과 유사한 잡음이나 클러터가 존재하는 경우 일반적인 임계화 기법을 적용하는 경우 표적의 오검출 위험이 매우 높다. 이러한 이유로 본 논문에서는 영상의 밝기 정보와 표적에 대한 사전 정보를 이용하여 최적의 표적 검출 결과를 도출하기 위한 적응적 임계화 기법을 제안한다. 소형 표적을 강조하기 위하여 인간 시각 시스템을 반영한 CSF(Contrast Sensitivity Function)를 적용하고, 표적이 강조된 영상에서 영상의 밝기 정보와 거리 정보를 이용하여 표적을 검출한다. 다양한 환경 조건에서 획득된 적외선 영상에 대한 실험 결과들은 제안 알고리즘의 견실한 성능을 보여준다.

• 로봇학회논문지
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• 제19권1호
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• pp.106-116
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• 2024

Ensuring robust 3D object detection is a core challenge for autonomous driving systems operating in urban environments. To tackle this issue, various 3D representation, including point cloud, voxels, and pillars, have been widely adopted, making use of LiDAR, Camera, and Radar sensors. These representations improved 3D object detection performance, but real-world urban scenarios with unexpected situations can still lead to numerous false positives, posing a challenge for robust 3D models. This paper presents a post-processing algorithm that dynamically adjusts object detection thresholds based on the distance from the ego-vehicle. While conventional perception algorithms typically employ a single threshold in post-processing, 3D models perform well in detecting nearby objects but may exhibit suboptimal performance for distant ones. The proposed algorithm tackles this issue by employing adaptive thresholds based on the distance from the ego-vehicle, minimizing false negatives and reducing false positives in the 3D model. The results show performance enhancements in the 3D model across a range of scenarios, encompassing not only typical urban road conditions but also scenarios involving adverse weather conditions.

• Journal of Positioning, Navigation, and Timing
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• 제1권1호
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• pp.15-21
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• 2012

For a GNSS receiver's robustness against RFI and the high accuracy of navigation solution in GNSS, interference source detection and mitigation are needed. In this paper, an adaptive lattice IIR notch filter is employed to track single-tone continuous wave and swept continuous wave interference signals, and an interference detection method is proposed. Furthermore, this paper presents interference source characterization algorithm using multiple ground stations' interference detection results. The measurement of the signal powers from each ground station is used to build weighting factors to estimate the type of the interference. The performance of interference detection algorithm is simulated for scenarios of GPS signal in the presence of single-tone continuous wave interference and swept continuous wave interference.