• 제목/요약/키워드: track error

검색결과 410건 처리시간 0.027초

적외선 영상에서 표적 추적을 위한 신호세기 기반 초기 유효게이트 설정 방법 (Setting an Initial Validation Gate based on Signal Intensity for Target Tracking in IR Image Sequences)

  • 양유경;김지은;이부환
    • 한국군사과학기술학회지
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    • 제17권1호
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    • pp.108-114
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    • 2014
  • This paper describes a method to set an intensity-based initial validation gate for tracking filter while preserves the ability of tracking a target with maximum speed. First, we collected real data set of signal versus distance of an airplane target. And at each data point, we computed maximum distance the target can move. And a function is modeled to expect the maximum moving pixels on the lateral direction based on the intensity of the detected target in IR image sequence. The initial prediction error covariance can be computed using this function to decide the size of the initial validation gate. The simulation results show the proposed method can set the appropriate initial validation gates to track the targets with the maximum speed.

모델 기반 설계 기법을 이용한 지능형 공조 장치의 이중 안전성 로직 연구 (A Study on the Fail Safety Logic of Smart Air Conditioner using Model based Design)

  • 김지호;김병우
    • 한국정밀공학회지
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    • 제28권12호
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    • pp.1372-1378
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    • 2011
  • The smart air condition system is superior to conventional air condition system in the aspect of control accuracy, environmental preservation and it is foundation for intelligent vehicle such as electric vehicle, fuel cell vehicle. In this paper, failure analyses of smart air condition system will be performed and then sensor fusion technique will be proposed for fail safety of smart air condition system. A sensor fusion logic of air condition system by using CO sensor, $CO_2$ sensor and VOC, $NO_x$ sensor will be developed and simulated by fault injection simulation. The fusion technology of smart air condition system is generated in an experiment and a performance analysis is conducted with fusion algorithms. The proposed algorithm adds the error characteristic of each sensor as a conditional probability value, and ensures greater accuracy by performing the track fusion with the sensors with the most reliable performance.

Premiums/Discounts, Tracking Errors and Performance of Saudi Arabian ETFs

  • DIAW, Alassane
    • The Journal of Asian Finance, Economics and Business
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    • 제6권2호
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    • pp.9-13
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    • 2019
  • The paper aims to investigate the performance of domestic Saudi Arabian ETFs. ETFs are investment vehicles in vogue. These instruments were the first levers for investors allowing them to enter some markets that have been highly protected or out of reach. Saudi Arabia, which has been promoted as an emerging country by MSCI, seeks to attract more foreign investors. The first ETFs were launched in the years 2010-2011. Even though their number has not increased since then, there is a desire to attract a large number of investors. We use premiums/discounts analysis, standard risk-return models, and tracking errors measurements to assess how closely their replicate the underlying benchmark based on monthly data. The results indicate that out of the three funds investigated two are slightly traded at premium, while the latter exhibit a price discount. However, tracking errors are at minimum for all funds suggesting that they track well the benchmark index. Further, the Jensen's model shows that alphas are negative or null, and betas capture largely the systematic risk which is consistent with index investing strategies. Finally, traditional risk-adjusted measures of performance are used to compare ETFs, and results exhibit negative ratios showing that portfolios achieve lower return than the risk-free rate.

Locking Time과 Jitter 특성의 개선을 위한 PLL 설계에 관한 연구 (A Study on the Design of PLL for Improving of Characteristics of Locking Time and Jitter)

  • 박재범;박윤식;김화영;성만영
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.2
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    • pp.1188-1191
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    • 2003
  • In this paper, we focus our attention on the improvement of locking time and jitter parameter and propose the new structure of PLL which combined with the FVC, FOVI Matcher(FVC-Output and VCO-input Matching Circuit), Control Circuit and the conventional charge pump PLL. Using fast operation characteristics of the FVC, the circuit matching FVC-Output and VCO-input (FOVI Matcher) made to synchronize very fast. Fast locking time is usually required for application where the PLL has to settle rapidly if they switch from an idle mode to a normal mode and to track high-frequency data bit rate in data recovery systems. After a fast acqusition is achieved by the using the FVC, the conventional PLL operates for removing the phase error between the reference signal and the feedback signal. Therefore this structure can improve the trade-off between acquisition behavior and locked behavior.

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소나 영상 촬영을 위한 자율항법 시스템 구현 (Implementation of AUSV System for Sonar Image Acquisition)

  • 류재훈;류광렬
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2016년도 추계학술대회
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    • pp.961-964
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    • 2016
  • 본 논문은 쏘나 영상 촬영을 위한 무인자율항법(AUSV Autonomous Unmanned Surface Vehicle) 시스템 개발에 관한 연구이다. 자율항법 시스템은 선체에 모션센서, DGPS에 의한 현재 경위도 좌표와 목표지 경위도 좌표의 차를 가지고 선체의 추진체(Thrusters)를 FF-PID 알고리즘으로 제어한다. 실험결과, 목적지 좌표에 대한 제어좌표 오차는 전체 항법거리 1km 에서 6 meter 이하이며, 자율항법 모드에서의 Sonar Image 촬영 결과물은 유인선 촬영 결과물과의 차이는 12 pixel 이하로 전체 영상 차이는 거의 식별할 수 없이 동일하다. 개발된 시스템은 유인선으로 촬영 불가능한 해저 지형에 대한 Sonar Image 촬영을 위한 새로운 방법으로 활용 가능하다.

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Visual Tracking Using Improved Multiple Instance Learning with Co-training Framework for Moving Robot

  • Zhou, Zhiyu;Wang, Junjie;Wang, Yaming;Zhu, Zefei;Du, Jiayou;Liu, Xiangqi;Quan, Jiaxin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권11호
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    • pp.5496-5521
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    • 2018
  • Object detection and tracking is the basic capability of mobile robots to achieve natural human-robot interaction. In this paper, an object tracking system of mobile robot is designed and validated using improved multiple instance learning algorithm. The improved multiple instance learning algorithm which prevents model drift significantly. Secondly, in order to improve the capability of classifiers, an active sample selection strategy is proposed by optimizing a bag Fisher information function instead of the bag likelihood function, which dynamically chooses most discriminative samples for classifier training. Furthermore, we integrate the co-training criterion into algorithm to update the appearance model accurately and avoid error accumulation. Finally, we evaluate our system on challenging sequences and an indoor environment in a laboratory. And the experiment results demonstrate that the proposed methods can stably and robustly track moving object.

정밀 도로지도 정보를 활용한 자율주행 하이브리드 제어 전략 (Hybrid Control Strategy for Autonomous Driving System using HD Map Information)

  • 유동연;김동규;최호승;황성호
    • 드라이브 ㆍ 컨트롤
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    • 제17권4호
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    • pp.80-86
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    • 2020
  • Autonomous driving is one of the most important new technologies of our time; it has benefits in terms of safety, the environment, and economic issues. Path following algorithms, such as automated lane keeping systems (ALKSs), are key level 3 or higher functions of autonomous driving. Pure-Pursuit and Stanley controllers are widely used because of their good path tracking performance and simplicity. However, with the Pure-Pursuit controller, corner cutting behavior occurs on curved roads, and the Stanley controller has a risk of divergence depending on the response of the steering system. In this study, we use the advantages of each controller to propose a hybrid control strategy that can be stably applied to complex driving environments. The weight of each controller is determined from the global and local curvature indexes calculated from HD map information and the current driving speed. Our experimental results demonstrate the ability of the hybrid controller, which had a cross-track error of under 0.1 m in a virtual environment that simulates K-City, with complex driving environments such as urban areas, community roads, and high-speed driving roads.

타이어 힘 추정을 위한 파라미터 최적화 파제카 모델과 인공 신경망 모델 간의 비교 연구 (A Comparative Study between the Parameter-Optimized Pacejka Model and Artificial Neural Network Model for Tire Force Estimation)

  • 차현수;김자유;이경수;박재용
    • 자동차안전학회지
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    • 제13권4호
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    • pp.33-38
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    • 2021
  • This paper presents a comparative study between the parameter-optimized Pacejka model and artificial neural network model for the tire force estimation. The two different approaches are investigated and compared in this study. First, offline optimization is conducted based on Pacejka Magic Formula model to determine the proper parameter set for the minimization of tire force error between the model and test data set. Second, deep neural network model is used to fit the model to the tire test data set. The actual tire forces are measured using MTS Flat-Track test platform and the measurements are used as the reference tire data set. The focus of this study is on the applicability of machine learning technique to tire force estimation. It is shown via the regression results that the deep neural network model is more effective in describing the tire force than the parameter-optimized Pacejka model.

Beam Tracking Method Using Unscented Kalman Filter for UAV-Enabled NR MIMO-OFDM System with Hybrid Beamforming

  • Yuna, Sim;Seungseok, Sin;Jihun, Cho;Sangmi, Moon;Young-Hwan, You;Cheol Hong, Kim;Intae, Hwang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권1호
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    • pp.280-294
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    • 2023
  • Unmanned aerial vehicles (UAVs) and millimeter-wave frequencies play key roles in supporting 5G wireless communication systems. They expand the field of wireless communication by increasing the data capacities of communication systems and supporting high data rates. However, short wavelengths, owing to the high millimeter-wave frequencies can cause problems, such as signal attenuation and path loss. To address these limitations, research on high directional beamforming technologies continue to garner interest. Furthermore, owing to the mobility of the UAVs, it is essential to track the beam angle accurately to obtain full beamforming gain. This study presents a beam tracking method based on the unscented Kalman filter using hybrid beamforming. The simulation results reveal that the proposed beam tracking scheme improves the overall performance in terms of the mean-squared error and spectral efficiency. In addition, by expanding analog beamforming to hybrid beamforming, the proposed algorithm can be used even in multi-user and multi-stream environments to increase data capacity, thereby increasing utilization in new-radio multiple-input multiple-output orthogonal frequency-division multiplexing systems.

MWIR 및 SWIR 센서를 이용한 커널상관필터기반의 표적추적 (Target Tracking based on Kernelized Correlation Filter Using MWIR and SWIR Sensors)

  • 선선구;이유리;서대교
    • 한국군사과학기술학회지
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    • 제26권1호
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    • pp.22-30
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    • 2023
  • When tracking small UAVs and drone targets in cloud clutter environments, MWIR sensors are often unable to track targets continuously. To overcome this problem, the SWIR sensor is mounted on the same gimbal. Target tracking uses sensor information fusion or selectively applies information from each sensor. In this case, parallax correction using the target distance is often used. However, it is difficult to apply the existing method to small UAVs and drone targets because the laser rangefinder's beam divergence angle is small, making it difficult to measure the distance. We propose a tracking method which needs not parallax correction of sensors. In the method, images from MWIR and SWIR sensors are captured simultaneously and a tracking error for gimbal driving is chosen by effectiveness measure. In order to prove the method, tracking performance was demonstrated for UAVs and drone targets in the real sky background using MWIR and SWIR image sensors.