• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.1
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• pp.10-17
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• 2013

This thesis proposes an automatic embedded core generator system that supports branch prediction. The proposed system includes a dynamic branch prediction module that enhances execution speed of target applications by inserting history/direction flags into BTAC(Branch Target Address Cache). Entries of BHT(Branch History Table) and BTAC are determined based on branch informations extracted by simulation. To verify the effectiveness of the proposed branch prediction module, ARM9TDMI core including a dynamic branch predictor was described in SMDL and generated. Experimental results show that as the number of entry rises, area increase up to 60% while application execution cycle and BTAC miss rate drop by an average of 1.7% and 9.6%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1304-1311
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• 2003

Target tracking in a real world situation is difficult problem because of continuous variations in images, huge amounts of data, and high processing speed demands. The problem becomes even harder in the case of sea background. This paper presents an initial study of neural network based method for target detection and tracking in cluttering environment. The approach uses a combination of differential motion analysis, Kohonen self-organizing network and region growing method. The network is capable of detecting the mass-centers of moving objects within one frame. The history of neurons positions in the sequential frames approximates the traces of the targets. The experiments done with the network in simulated environment showed promising results.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.78-87
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• 1989

In this paper, a spatio-temporal gradient (STG) method with generalized least square estimation (GLSE) is proposed for the detection of an object motion in an image sequence corrupted by white Gaussian noise. The proposed method is applied to an automatic target tracker using a high speed 16-bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has much better performance over the conventional one with least square estimation (LSE).

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.148-155
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• 2015

The Levenberg-Marquardt method is a well known solution about the least square problem. However, in a Target Motion Analysis(TMA) application most of researches have used the Gauss-Newton method as a batch estimator, which of inverse matrix calculation may causes instability problem. In this paper, Levenberg-Marquardt method is applied to TMA problem to prevent its divergence. In experiment, its performance is compared with Gauss-Newton in domain of range, course and speed. Monte Carlo simulation reveals the convergence time and reliability of the TMA based on Levenberg-Marquardt.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.209-216
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• 2015

It is difficult to detect, track and intercept ballistic missile because of its high speed and short flight time from launching to target area. In order to increase the success rate of a ballistic missile interceptor, it is important to track the flight trajectory for a long time after the detection in the early launch. Radar Cross Section(RCS) of the target is important when the target to be detected by the radar, and the difference between the RCS value greatly changes depending on the viewing direction during the flight missile trajectory. In this paper, it is assumed that a ballistic missile is launched at east coast of North Korea, observe that missile by a land based radar and sea deployed radar. And it is analyzed and compared that RCS difference of ballistic missile.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.2
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• pp.114-120
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• 2011

This paper presents a cooperative standoff tracking of a moving target using multiple unmanned aircraft. To provide guidance commands, vector fields are designed utilizing the Lyapunov stability theory. A roll angle command is generated to keep a constant distance from the target in a circular motion. A speed command and a heading angle command are designed to keep a constant phase angle with respect to the front aircraft and to prevent a collision between aircraft. Numerical simulation is performed to verify the tracking and collision performance of the proposed control laws.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1183-1202
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• 2017

Image restoration has been carried out by texture synthesis mostly for large regions and inpainting algorithms for small cracks in images. In this paper, we propose a new approach that allows for the simultaneous fill-in of different structures and textures by processing in a wavelet domain. A combination of structure inpainting and patch-based texture synthesis is carried out, which is known as patch-based inpainting, for filling and updating the target region. The wavelet transform is used for its very good multiresolution capabilities. The proposed algorithm uses the wavelet domain subbands to resolve the structure and texture components in smooth approximation and high frequency structural details. The subbands are processed separately by the prioritized patch-based inpainting with isophote energy driven texture synthesis at the core. The algorithm automatically estimates the wavelet coefficients of the target regions of various subbands using optimized patches from the surrounding DWT coefficients. The suggested performance improvement drastically improves execution speed over the existing algorithm. The proposed patch optimization strategy improves the quality of the fill. The fill-in is done with higher priority to structures and isophotes arriving at target boundaries. The effectiveness of the algorithm is demonstrated with natural and textured images with varying textural complexions.

• 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.

• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.320-326
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• 2020

The present study aimed to assess the longitudinal connectivity owing to migrant characteristics of the target fish. The study area was Wonju-cheon Stream, and the target species were Zacco platypus and Minnows. The HEC-RAS model was used for the computation of the flow, and the ICE (Information sur la Continuite Ecologique) method was used to analyze the longitudinal connectivity. The longitudinal connectivity was assessed using the minimum overflow height, velocity, and depth of the cross sectional structure of a plunge pool and considering the swimming speed of the target fish. Simulation results indicated that the longitudinal connectivity scores for the Zacco platypus and Minnows were approximately 76 and 23, respectively.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.338-345
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• 2024

Magnetic anomaly signals from the ferromagnetic targets such as ships in the sea are measured by drone-based magnetic anomaly detection. A quantum magnetometer is suspended from the drone by 4 strings. Flight altitude and speed of drone are 100 m and 5 m/s, respectively. We obtain magnetic anomaly signals of few nT from the ships clearly. We analyze the signal characteristics by the ferromagnetic target through simulation using COMSOL multiphysics.