• Title/Summary/Keyword: Tracking Method

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Research of the Unmanned Vehicle Control and Modeling for Lane Tracking (차선인식을 위한 무인자동차의 차량제어 및 모델링에 관한 연구)

  • 김상겸;임하영;김정하
    • Transactions of the Korean Society of Automotive Engineers
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    • v.11 no.6
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    • pp.213-221
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    • 2003
  • This paper describes a method of lane tracking by means of a vision system which includes vehicle control and modeling. Lane tracking is considered one of the important technologies in an unmanned vehicle and mobile robot system. The current position and condition of the vehicle are calculated from an image processing method by a CCD camera. We deal with lane tracking as follows. First, vehicle control is included in the road model, and lateral and longitudinal controls. Second, the image processing method deals with the lane detection method, image processing algerian, and filtering method. Finally, this paper proposes a correct method for lane detection through a vehicle test by wireless data communication.

Development of New Algorithm for Maximum Power Point Tracking of Photovoltaic system (Photovoltaic 시스템의 MPPT를 위한 새로운 알고리즘 개발)

  • Park, Ki-Tae;Ko, Jae-Sub;Choi, Jung-Sik;Park, Byung-Sang;Chung, Dong-Hwa
    • Journal of Korean Institute of Fire Investigation
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    • v.10 no.1
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    • pp.87-95
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    • 2007
  • This paper is proposed a novel method to approximate the maximum power for a photovoltaic inverter system and tracking method. It is designed for power systems application and utilities. The proposed Maximum Power Point Tracking (MPPT) control has the advantage to provide a new simple way to approximate the optimal or rated voltage, the optimal or rated current and maximum power rating produced by a solar panel and the photovoltaic inverter. And this straightforward method will be named linear reoriented coordinates method (LRCM) with the advantage that Pmax and $V_{op}$ can be approximated using the same variable as the dynamic model without using complicate approximations or Taylor series. Furthermore tracking method is improved over 50% photovoltaic efficiency. This paper is proposed MPPT using LRMC and tracking method using weather condition of domestic moderate program technique. This paper is proposed the experimental results to verify the effectiveness of the new methods.

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Development of a novel tracking for efficiency improvement of PV system with sensor method (센서방식 태양광 발전시스템의 효율개선을 위한 새로운 추적알고리즘 개발)

  • Jang, Mi-Geum;Ko, Jae-Sub;Choi, Jung-Sik;Kang, Sung-Jun;Back, Jung-Woo;Chung, Dong-Hwa
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2009.05a
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    • pp.424-427
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    • 2009
  • This paper reposes a novel tracking algerian for efficiency improvement of photovoltaic(PV) system using sensor method PV system of sensor method is exactly impossible to track a sun position when insolation is low or rapidly changed by the clouds and fogs. Also, in this case, tracking device is occurred energy consumption by unnecessary operating. This statement of reason, real power of PV system is not increased than fixed PV system in specified location. Therefore, this paper proposes a novel ticking algorithm considered insolation for efficiency improvement of PV system using sensor method And this paper analyzes the generation volume and proves the validity of proposed algorithm as compared with the conventional PV tracking system using sensor method.

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Particle Filtering based Object Tracking Method using Feedback and Tracking Box Correction (피드백과 박스 보정을 이용한 Particle Filtering 객체추적 방법론)

  • Ahn, Jung-Ho
    • Journal of Satellite, Information and Communications
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    • v.8 no.1
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    • pp.77-82
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    • 2013
  • The object tracking method using particle filtering has been proved successful since it is based on the Monte Carlo simulation to estimate the posterior distribution of the state vector that is nonlinear and non-Gaussian in the real-world situation. In this paper, we present two nobel methods that can improve the performance of the object tracking algorithm based on the particle filtering. First one is the feedback method that replace the low-weighted tracking sample by the estimated state vector in the previous frame. The second one is an tracking box correction method to find an confidence interval of back projection probability on the estimated candidate object area. An sample propagation equation is also presented, which is obtained by experiments. We designed well-organized test data set which reflects various challenging circumstances, and, by using it, experimental results proved that the proposed methods improves the traditional particle filter based object tracking method.

A Method of Tracking Object using Particle Filter and Adaptive Observation Model

  • Kim, Hyoyeon;Kim, Kisang;Choi, Hyung-Il
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.1
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    • pp.1-7
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    • 2017
  • In this paper, we propose an efficient method that is tracking an object in real time using particle filter and adaptive observation model. When tracking object, it happens object shape variation by camera or object movement in variety environments. The traditional method has an error of tracking from these variation, because it has fixed observation model about the selected object by the user in the initial frame. In order to overcome these problems, we propose a method that updates the observation model by calculating the similarity between the used observation model and the eight-way of edge model from the current position. If the similarity is higher than the threshold value, tracking the object using updated observation model to reset observation model. On the contrary to this, the algorithm which consists of a process is to maintain the used observation model. Finally, this paper demonstrates the performance of the stable tracking through comparison with the traditional method by using a number of experimental data.

Application of Neural Network Control Algorithm and Maximum Power Tracking of Sun Photocell using Sunlight Sensor (태앙광 센서에 의한 태앙광 전지의 최대전력추적과 신경회로망 제어알고리즘 적용)

  • Yoo, Seok-Ju;Lee, Seong-Su;Park, Wal-Seo
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.24 no.2
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    • pp.33-38
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    • 2010
  • Recently, photovoltaic generator system is widely extended by energy policy of the government. Add to this, high efficiency of photocell power generation is steady needed to sun tracking method. However sun tracking method is not widely extended by insufficiency of tracking technology. As method of solving this problem, this paper applied sunlight sensor and neural network control algorithm for maximum power tracking of sun photocell. Sun tracking sensor consists of one upright square pole and form light sensor of east, west, south, north on flat board. Sun tracking dual axes control is operated respectively by two motor. Motor control input is calculated by neural network control algorithm. The function of proposed control method is verified by sun tracking experiment of photocell generation. The sun tracking method of this paper is increased 32[%] efficiency more than fixed method.

Analysis of Tracking Accuracy with Consideration of Fighter Radar Measurement Characteristics (전투기 레이다 측정 특성을 고려한 추적정확도 분석)

  • Seo, Jeongjik
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.29 no.8
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    • pp.640-647
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    • 2018
  • This study analyzes the tracking accuracy(tracking errors) of fighter radar. Measurement error, detection failure, and radar cross section(RCS) fluctuation in radar measurements degrade the measurement quality and hence affect the tracking accuracy. Therefore, these radar measurement characteristics need to be considered when analyzing the tracking accuracy. In this paper, a method for analyzing the tracking accuracy is proposed; this method considers the detection error, detection probability, and RCS fluctuation. Results from experiments conducted with the proposed method show that the detection probability and RCS fluctuation affect tracking accuracy.

Robust Generalized Labeled Multi-Bernoulli Filter and Smoother for Multiple Target Tracking using Variational Bayesian

  • Li, Peng;Wang, Wenhui;Qiu, Junda;You, Congzhe;Shu, Zhenqiu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.908-928
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    • 2022
  • Multiple target tracking mainly focuses on tracking unknown number of targets in the complex environment of clutter and missed detection. The generalized labeled multi-Bernoulli (GLMB) filter has been shown to be an effective approach and attracted extensive attention. However, in the scenarios where the clutter rate is high or measurement-outliers often occur, the performance of the GLMB filter will significantly decline due to the Gaussian-based likelihood function is sensitive to clutter. To solve this problem, this paper presents a robust GLMB filter and smoother to improve the tracking performance in the scenarios with high clutter rate, low detection probability, and measurement-outliers. Firstly, a Student-T distribution variational Bayesian (TDVB) filtering technology is employed to update targets' states. Then, The likelihood weight in the tracking process is deduced again. Finally, a trajectory smoothing method is proposed to improve the integrative tracking performance. The proposed method are compared with recent multiple target tracking filters, and the simulation results show that the proposed method can effectively improve tracking accuracy in the scenarios with high clutter rate, low detection rate and measurement-outliers. Code is published on GitHub.

A Novel PV Tracking System Control Considering the Power Loss with Change of Insolation (일사량 변화에 다른 전력손실을 고려한 새로운 태양광 추적 시스템 제어)

  • Park, Ki-Tae;Choi, Jung-Sik;Chung, Dong-Hwa
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.22 no.6
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    • pp.89-99
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    • 2008
  • In this paper proposes a novel tacking algorithm regarding the power loss when operating a tracking system for a rapidly changing insolation to improve the power of PV hacking system. The tracking system of sensor method used in a conventional PV power station is unable to exactly track a sun position when lacking in the intensity of radiation and has the problem is malfunction of tracking system by a rapidly changing climatic. The tracking system of program method spends too much energy on the unnecessary operation of tracking system because that is unable to adapt itself to a outside factor of climatic environment. In case of tracking an azimuth and altitude of the sun in realtime, therefore, the actual PV power is less increasing than the power of tracking system fixed a specific position. To reduce the power loss, this pap proposes a novel control algorithm of the tracking system. Also, this paper is analyzed efficiency of traditional solar tracking method and proposed method, prove validity of proposed algorithm through demonstrable study.

Research of the Unmanned Vehicle Control and Modeling for Lane Tracking and Obstacle Avoidance

  • Kim, Sang-Gyum;Lee, Woon-Sung;Kim, Jung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.932-937
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    • 2003
  • In this paper, we will explain about the unmanned vehicle control and modeling for combined obstacle avoidance and lane tracking. First, obstacle avoidance is considered as one of the important technologies in the unmanned vehicle. It is consisted by two parts: the first part includes the longitudinal control system for the acceleration and deceleration and the second part is the lateral control system for the steering control. Each system uses to the obstacle avoidance during the vehicle moving. Therefore, we propose the method of vehicle control, modeling and obstacle avoidance. Second, we describe a method of lane tracking by means of vision system. It is important in the unmanned vehicle and mobile robot system. In this paper, we deal with lane tracking and image processing method and it is including lane detection method, image processing algorithm and filtering method.

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