• 한국항공운항학회지
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• 제21권1호
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• pp.23-29
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• 2013

This paper presents a tracking filter of radar beacon system (RBS) for automatic takeoff and landing of an unmanned aerial vehicle. The proposed tracking filter is designed as the decoupled tracking filter to reduce the computational burden. Also, an adaptive estimation method of the measurement error covariance is proposed to provide an improved tracking performance compared to the conventional decoupled tracking filter whenever the accuracy of RBS observations is degraded. 100 times Monte Carlo runs performed to analyze the performance of the proposed tracking filter in case of normal operation and degraded operations, respectively. The simulation results show that the proposed tracking filter provides the improved tracking accuracy in comparison with the conventional decoupled tracking filter.

• 반도체디스플레이기술학회지
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• 제10권2호
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• pp.25-30
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• 2011

This paper presents a tracking vibration estimation system of the track-following system using a tracking loop gain adjustment algorithm and a genetic algorithm. The algorithms are introduced to estimate accurately the tracking vibration quantity in spite of the uncertainties of the tracking actuator. An estimated actuator model can be found by applying a genetic algorithm. Accordingly, the tracking vibration quantity can be estimated from the measured tracking error, the tracking controller and the estimated actuator model. The proposed tracking vibration estimation method is applied to the track-following system of an optical recording device and is evaluated through the experimental result.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.56-56
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• 2000

In this paper, the relationship between GPS code and carrier tracking performance is given. Through the error analysis and experiments, the performance of code tracking loop can be improved using narrow correlation. The performance of code tracking loop can be also improved if the better carrier tracking loop is used. On the other hand, the performance of carrier tracking loop is independent of that of code tracking loop.

• 제어로봇시스템학회논문지
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• 제14권9호
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• pp.939-947
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• 2008

The GPS tracking loop consists of three parts in general: discriminator, loop filter and DCO (Digitally Controlled Oscillator). The loop filter is the main part of the tracking loop designed to ensure a good tracking performance. Generally, the loop filter is designed using classical PI(Proportional Integral) control. Although the carrier Doppler and code Doppler are generated by the same relative movement between the satellite and the user, often, the loop filters for each tracking loop are designed separately and independently. Sometimes, they are used in a combined manner such as carrier aided code tracking, FLL assisted PLL, etc. For better GPS signal tracking, we need to design the FLL/PLL/DLL altogether optimally. The purpose of this paper is to design a GPS receiver tracking loop based on the Kalman filter in a combined manner. Also, the proposed GPS receiver tracking loop is compared with a conventional tracking loop in terms of the transfer function and the DCO input. This paper shows that conventional tracking loop is equal to the Kalman filter based tracking loop.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1066-1079
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• 2023

Multi-target tracking based on the detector is a very hot and important research topic in target tracking. It mainly includes two closely related processes, namely target detection and target tracking. Where target detection is responsible for detecting the exact position of the target, while target tracking monitors the temporal and spatial changes of the target. With the improvement of the detector, the tracking performance has reached a new level. The problem that always exists in the research of target tracking is the problem that occurs again after the target is occluded during tracking. Based on this question, this paper proposes a DeepSORT model based on SIFT features to improve ship tracking. Unlike previous feature extraction networks, SIFT algorithm does not require the characteristics of pre-training learning objectives and can be used in ship tracking quickly. At the same time, we improve and test the matching method of our model to find a balance between tracking accuracy and tracking speed. Experiments show that the model can get more ideal results.

• 전기학회논문지
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• 제59권4호
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• pp.779-787
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• 2010

In this paper, We introduce electrical tracking generated from surface activity associated with flow of leakage current on insulator under wet and contaminated conditions and design electrical tracking pattern recognition system by using LabVIEW. We measure the leaking current of contaminated wire by using LabVIEW software and the NI-c-DAQ 9172 and NI-9239 hardware. As pattern recognition algorithm and optimization algorithm for electrical tracking system, neural networks, Radial Basis Function Neural Networks(RBFNNs) and particle swarm optimization are exploited. The designed electrical tracking recognition system consists of two parts such as the hardware part of electrical tracking generator, the NI-c-DAQ 9172 and NI-9239 hardware and the software part of LabVIEW block diagram, LabVIEW front panel and pattern recognition-related application software. The electrical tracking system decides whether electrical tracking generate or not on electrical wire.

• Journal of Power Electronics
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• 제10권4호
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• pp.405-411
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• 2010

This paper proposes a novel tracking algorithm considering radiation to improve the power of a photovoltaic (PV) tracking system. The sensor method used in a conventional PV plant is unable to track the sun's exact position when the intensity of solar radiation is low. It also has the problem of malfunctions in the tracking system due to rapid changes in the climate. The program method generates power loss due to unnecessary operation of the tracking system because it is not adapted to various weather conditions. This tracking system does not increase the power above that of a power of tracking system fixed at a specific position due to these problems. To reduce the power loss, this paper proposes a novel control algorithm for a tracking system and proves the validity of the proposed control algorithm through a comparison with the conventional PV tracking method.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.1017-1028
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• 2019

Pedestrian tracking is a particular object tracking problem and an important component in various vision-based applications, such as autonomous cars and surveillance systems. Following several years of development, pedestrian tracking in videos remains challenging, owing to the diversity of object appearances and surrounding environments. In this research, we proposed a tracking-by-detection system for pedestrian tracking, which incorporates a convolutional neural network (CNN) and color information. Pedestrians in video frames are localized using a CNN-based algorithm, and then detected pedestrians are assigned to their corresponding tracklets based on similarities between color distributions. The experimental results show that our system is able to overcome various difficulties to produce highly accurate tracking results.

• ETRI Journal
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• 제45권3호
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• pp.394-403
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• 2023

Direct tracking problem of moving noncircular sources for multiple arrays is investigated in this study. Here, we propose an improved unscented particle filter (I-UPF) direct tracking method, which combines system proportional symmetry unscented particle filter and Markov Chain Monte Carlo (MCMC) algorithm. Noncircular sources can extend the dimension of sources matrix, and the direct tracking accuracy is improved. This method uses multiple arrays to receive sources. Firstly, set up a direct tracking model through consecutive time and Doppler information. Subsequently, based on the improved unscented particle filter algorithm, the proposed tracking model is to improve the direct tracking accuracy and reduce computational complexity. Simulation results show that the proposed improved unscented particle filter algorithm for noncircular sources has enhanced tracking accuracy than Markov Chain Monte Carlo unscented particle filter algorithm, Markov Chain Monte Carlo extended Kalman particle filter, and two-step tracking method.

• 대한기계학회논문집A
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• 제27권5호
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• pp.697-704
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• 2003

In this paper, the visual tracking system for arbitrary shaped moving object is proposed. The established tracking system can be divided into model based method that needs previous model for target object and image based method that uses image feature. In the model based method, the reliable tracking is possible, but simplification of the shape is necessary and the application is restricted to definite target mod el. On the other hand, in the image based method, the process speed can be increased, but the shape information is lost and the tracking system is sensitive to image noise. The proposed tracking system is composed of the extraction process that recognizes the existence of moving object and tracking process that extracts dynamic characteristics and shape information of the target objects. Specially, active contour model is used to effectively track the object that is undergoing shape change. In initializatio n process of the contour model, the semi-automatic operation can be avoided and the convergence speed of the contour can be increased by the proposed effective initialization method. Also, for the efficient solution of the correspondence problem in multiple objects tracking, the variation function that uses the variation of position structure in image frame and snake energy level is proposed. In order to verify the validity and effectiveness of the proposed tracking system, real time tracking experiment for multiple moving objects is implemented.