• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11A
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• pp.1078-1084
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• 2010

The tracking performance of a big parabola tracking antenna system for tracking and receiving of the signal from the vehicle is impacted by many factors of the internal and the external of the system. In this paper, we analyze the tracking error due to the radio refraction in the application of the tracking and positioning of the vehicle by using radio frequency. The real measurement data are used for the analysis which had been acquired by using GPS and the tracking systems of C- and S-band frequencies in NARO Space centre. To verify the correlation between the tracking errors measured and the radio refraction, we review the error factors and the accuracies of the tracking systems, and the characteristics of the refractivity. The analysis shows that there are angular errors which are due to the radio refraction and not to be neglected, compared to the accuracies of the tracking systems, in case of low elevation angle less than 10 degrees. Also, the tracking errors depend on the target altitude as well as the elevation angle for the case of the target in the troposphere. It is recommended to correct the tracking angle considering the target altitude and elevation angle for the precise target positioning.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.163-169
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• 2021

In this paper, we implemented a deep learning-based automatic object tracking and handy motion control drone system and analyzed the performance of the proposed system. The drone system automatically detects and tracks targets by analyzing images obtained from the drone's camera using deep learning algorithms, consisting of the YOLO, the MobileNet, and the deepSORT. Such deep learning-based detection and tracking algorithms have both higher target detection accuracy and processing speed than the conventional color-based algorithm, the CAMShift. In addition, in order to facilitate the drone control by hand from the ground control station, we classified handy motions and generated flight control commands through motion recognition using the YOLO algorithm. It was confirmed that such a deep learning-based target tracking and drone handy motion control system stably track the target and can easily control the drone.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.47-55
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• 2023

Recently, Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. The UWS is a technology that uses an ultrasonic sensor to detect objects at short distances. While it has the advantage of being simple to use, it also has the disadvantage of having a limited detection distance. The LDWS, on the other hand, is a technology that uses front image processing to detect lane departure and ensure the safety of the driving path. However, it may not be sufficient for determining the driving environment around the vehicle. To overcome these limitations, a system that utilizes FMCW radar is being used. The BSD radar system using FMCW continuously emits signals while driving, and the emitted signals bounce off nearby objects and return to the radar. The key technologies involved in designing the BSD radar system are tracking algorithms for detecting the surrounding situation of the vehicle. This paper presents a tracking algorithm for designing a BSD radar system, while explaining the principles of FMCW radar technology and signal types. Additionally, this paper presents the target tracking procedure and target filter to design an accurate tracking system and performance is verified through simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.3
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• pp.33-40
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• 2006

In towed array passive sonar system, sonar operators cannot detect and track the all targets simultaneously in the omni-directional area by just Operator Initiated Tracking(OIT). In this paper, omni-directional automatic target detection and tracking algorithm is described and optimize the parameters through ocean data to overcome the drawbacks of OITs. The algorithm is verified through sea trials with submarines.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.21-30
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• 2007

A practical method to design the input shaping which generates control command is proposed in this paper, We suggest an experimental technique considering human operator's target tracking error to improve aiming accuracy which significantly affects hit probability. It is known that stabilization performance is one of the most important factors for ground combat vehicle system. In particular, stabilization error of the manual target tracking system mounted on moving vehicle directly affects hit probability. To reduce this error, we applied input command shaping method using preprocessing filtering and functional curve fitting. First of all, we construct the human operator model to consider effects of human operator on our system. Input shaping curve is divided into several regions to get rid of the above problems and to improve the system performance. At example design part, we chose three steps of functional command curve and determine the parameters of the function by the proposed design method. In order to verify the proposed design method, we carried out the experiments with real plant of a fighting vehicle.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.217-222
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• 2021

EOTS(Electro-Optical Tracking System) is utilized in acquiring visual information to assess a guided missile's performance. As the missile travels so fast, it is almost impossible for operator to re-capture the lost target. The RADAR or telemetry data are used to re-capture the lost target however facilities to receive real time data is required, which constrains selection of tracking site. Unlike aforementioned data, pre-calculated nominal trajectory can be used without communication facility. This paper proposes a method to predict lost target's state by employing nominal trajectory. Firstly, observed trajectory and nominal trajectory are compared using DTW and current target's state is predicted. The predicted state is used as observation in Kalman filter's correction phase to predict target's next state. The plausibility of the proposed method is verified by applying on actual missile trajectory.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.22-26
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• 1998

This paper proposes a simple method to measure system's performance in target tracking problems. Essentially employing the Cramer-Rao Lower Bound (CRLB) on tracking accuracy, an algorithm of predicting system's performance under various scenarios is developed. The input data is a collection of measurements over tim from sensors embedded in Gaussian noise. The target of interest may not maneuver over the processing time interval while the own ship observing platform may maneuver in an arbitrary fashion. The proposed approach is demonstrated and discussed through simulation results.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1203-1204
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• 2008

In this paper, a new stereo object tracking system using the disparity motion vector is proposed. In the proposed method, the time-sequential disparity motion vector can be estimated from the disparity vectors which are extracted from the sequence of the stereo input image pair and then using these disparity motion vectors, the area where the target object is located and its location coordinate are detected from the input stereo image. Basing on this location data of the target object, the pan/tilt embedded in the stereo camera system can be controlled and as a result, 3D tracking of the target object can be possible.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.696-701
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• 2004

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion, have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.209-216
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• 2012

In this paper, we propose a novel tracking method which uses image features consisted of the area, average intensity, aspect ratio of a target image for the real-time IR surveillance system. The image features of the ground target can be modeled as a random process with exponential autocorrelation function mathematically. Finally, we derived a discrete target dynamic equation including kinematic states and geometric states of the target. Simulation results shows that the performance of the proposed method is better than that of the previous tracking method.