• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1031-1038
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• 2016

In the UAVs, the position error of the inertial navigation system is constantly increased when global positioning system goes wrong due to interference. It makes impossible to ensure mission and flight safety. If the data-link system provide the position of the UAV for inertial navigation system periodically, then the UAV may operate normally under malfunction of the global positioning system. In this paper, we introduce an algorithm for estimating the position of the UAV using the monopulse tracking and distance measurement of the line-of-sight data-link system. Also, we propose a method to improve the performance of position estimation. And we assured ourselves that this method can be applied in the UAVs.

• The Journal of the Acoustical Society of Korea
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• v.26 no.5
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• pp.220-226
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• 2007

The two major objectives of acoustical measurements in a cavitation tunnel are measuring the noise levels generated by rotating propellers behind a hull and localizing possible noise sources in order to reduce noise levels. Propeller noise measurement experiments were performed in MOERI cavitation tunnel at December, 2006. In order to put the propeller into cavitating conditions, a wake-generating dummy body was devised. In addition, ten hydrophones are put inside a wing-shaped casing in order to minimize the unexpected flow induced self noise around hydrophone itself. After measuring both of the noises of the rotating propeller behind the dummy body and signals generated by a virtual source, respectively the data were matched field processed using the frequency incoherent Bartlett processor to localize noises on the propeller plane. In this paper, we presented the measured noise analysis and the localization results.

• Journal of IKEEE
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• v.15 no.1
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• pp.76-85
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• 2011

In this paper, we analysed RSS characteristics by external factors and presented an efficient algorithm for real-time location tracking and its hardware system. The proposed algorithm enhanced the ranging accuracy using Kalman Filter based on the RSS DB. The location tracking system that consists of the tag, AP(Access Point), a data collector(Data Receiver) with IEEE 802.15.4(ZigBee) network environment, and location tracking application that reveal locations of each tag is implemented for the test environment. The location tracking system presented in this paper is implemented with MSP430 microprocessor manufactured by TI(Texas Instrument), CC2420 RF chipset and the location tracking application. With the results of the experiment, the proposed algorithm and the system can achieve the efficiency and the accuracy of location tracking with the average error of 19.12cm, and its standard deviation of 5.31cm in outdoor circumstance. Also, the experimental result shows that exact tracking of position in indoor circumstance cannot achieve because of vulnerable RSS with external circumstance.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.15-29
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• 2018

This paper proposes an enhanced object tracking algorithm to compensate the lack of temporal information in existing particle swarm optimization based object trackers using the trajectory of the target object. The proposed scheme also enables the tracking and documentation of the location of an online updated set of distractions. Based on the trajectories information and the distraction set, a rule based approach with adaptive parameters is utilized for occlusion detection and determination of the target position. Compare to existing algorithms, the proposed approach provides more comprehensive use of available information and does not require manual adjustment of threshold values. Moreover, an effective weight adjustment function is proposed to alleviate the diversity loss and pre-mature convergence problem in particle swarm optimization. The proposed weight function ensures particles to search thoroughly in the frame before convergence to an optimum solution. In the existence of multiple objects with similar feature composition, this algorithm is tested to significantly reduce convergence to nearby distractions compared to the other existing swarm intelligence based object trackers.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.365-367
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• 2013

해상감시레이더는 관제지역의 해상교통정보를 수집하는 해상교통관제시스템의 주요 센서로, 다양한 운동 특성을 갖는 선박의 안정적인 추적과 위치, 속도, 침로 등의 정확한 정보를 제공하는 것은 VTS 성능 개선 및 서비스 고도화에 매우 중요한 요소 기술이다. 본 논문에서는 해상교통관제시스템에서 다양한 기동 특성을 갖는 선박의 정확한 추적을 위하여 상호작용 다중필터(IMM) 추정기를 이용한 추적 알고리즘을 설계하고, 모의실험을 통하여 필터 뱅크의 구성에 따른 성능 비교 및 분석을 수행한다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.30-33
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• 2003

영상 검지기를 통한 차량 탐지 방법은 날씨와 같은 환경에 민감하게 반응하여 차량의 미탐지 및 오탐지가 발생하게 된다. 이를 해결하기 위해 다양한 일기조건하에서 차량 추적 방법에 대해 제안한다. 다양한 일기 조건하에서의 차량 추적은 눈, 비, 안개 환경에서 각 날씨의 특징을 분석, 반영하여 차량을 탐지하고 추적한다. 눈이 내리는 환경에서는 눈이 카메라 가까이에서 차량 blob으로 잘못 탐지되는 blob을 제거하기 위해 카메라와의 거리에 따른 실제 크기를 구하는 size filtering 방법을 사용한다. 비, 안개 환경에서는 흐릿해진 영상 때문에 차량이 교통신호등에 의해 차량 정체시 여러 차량이 하나의 blob으로 탐지되는 문제점을 해결하기 위해 이전 영상에서의 차량 위치 정보를 이용한 재 blob화 방법을 사용한다.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.817-826
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• 2012

This paper presents a robust viewpoint estimation algorithm for Moving Parallax Barrier mobile 3D display in sudden illumination changes. We analyze the previous viewpoint estimation algorithm that consists of the Viola-Jones face detector and the feature tracking by the Optical-Flow. The sudden changes in illumination decreases the performance of the Optical-flow feature tracker. In order to solve the problem, we define a novel performance measure for the Optical-Flow tracker. The overall performance can be increased by the selective adoption of the Viola-Jones detector and the Optical-flow tracker depending on the performance measure. Various experimental results show the effectiveness of the proposed method.

• Journal of Korea Spatial Information System Society
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• v.7 no.2 s.14
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• pp.67-79
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• 2005

For tracing tag locations, the trajectories should be modeled and indexed in a radio frequency identification (RFID) system. The trajectory of a tag is represented as a line that connects two spatiotemporal locations captured when the tag enters and leaves the vicinity of a reader. If a tag enters but does not leave a reader, its trajectory is represented only as a point captured at entry. Because the information that a tag stays in a reader is missing from the trajectory represented only as a point, it is impossible to find the tag that remains in a reader. To solve this problem we propose the data model in which trajectories are defined as intervals and new index scheme called the Interval R-tree. We also propose new insert and split algorithms to enable efficient query processing. We evaluate the performance of the proposed index scheme and compare it with the R-tree and the R*-tree. Our experiments show that the new index scheme outperforms the other two in processing queries of tags on various datasets.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.377-385
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• 2015

This paper proposes a novel forward vehicle tracking algorithm based on the WMIL(Weighted Multiple Instance Learning) equipped with a particle filter. In the proposed algorithm Haar-like features are used to train a vehicle object detector to be tracked and the location of the object are obtained from the recognition result. In order to combine both the WMIL to construct the vehicle detector and the particle filter, the proposed algorithm updates the object location by executing the propagation, observation, estimation, and selection processes involved in particle filter instead of finding the credence map in the search area for every frame. The proposed algorithm inevitably increases the computation time because of the particle filter, but the tracking accuracy was highly improved compared to Ababoost, MIL(Multiple Instance Learning) and MIL-based ones so that the position error was 4.5 pixels in average for the videos of national high-way, express high-way, tunnel and urban paved road scene.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.4
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• pp.401-409
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• 2004

A monitoring system for container using CPS is the system for positioning and managing containers in real time. CPS is capable of positioning the container, promptly with a reasonable amount of accuracy. Facility managers of ports or airports should have loading, unloading, and keeping freight effectively. Transport companies or freight owners should allocate moving container properly and be able to prevent the loss or delay of freight. In this study, the position and pathways of container are monitored by real-time tracking method. The absolute and relative locations of container are monitored digitally and visually from TC_loading to TC_unloading yard. It has been tested the movement of the containers equiped with GPS, and its accuracy and efficiency were analyzed.