• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.120-124
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• 1991

In this paper, we consider the maneuvering detection and target tracking problem in uncertain linear discrete-time systems. The maneuvering detection is based on X$^{2}$ test[2,71, where Kalman filters have been utilized so far. The target tracking is performed by the maneuvering input compensation based on a maximum likelihood estimator. KF has been known to diverge when some modelling errors exist and fail to detect the maneuvering and to track the target in uncertain systems. Thus this paper adopt the FIR filter[l], which is known to be robust to modelling errors, for maneuvering detection and target tracking problem. Various computer simulations show the superior performance of the FIR filter in this problem.

• Journal of Korea Ship Safrty Technology Authority
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• s.36
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• pp.71-78
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• 2014

If we don't know the intention of altering course of a target ship when being in a head-on or a crossing situation, we may be confused about our decision making to change our course for collision avoidance and be in a danger of collision. In order to solve these problems, we need to develop an automatic detection system on altering course of a target ship for efficient collision avoidance. In this paper, we proposed an early detection system on altering course of a target ship using the steering wheel signal. This system will contribute to the reduction of collision accidents and also be used to the VTS system and the analysis of marine accidents.

• Journal of Sensor Science and Technology
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• v.18 no.3
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• pp.190-196
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• 2009

In a conventional camera system, a target tracking system consists of a camera part and a image processing part. However, in the field of the real time image processing, the vision chip for edge detection which was made by imitating the algorithm of humanis retina is superior to the conventional digital image processing systems because the human retina uses the parallel information processing method. In this paper, we present a high speed target tracking system using the function of the CMOS vision chip for edge detection.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.355-365
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• 2000

The interferometric correlation, or coherence, is calculated to measure the variance of the interferometric phase and amplitude within the neighbourhood of any location within the image at a result of SAR (Synthetic Aperture Radar) interferometric process which utilizes the phase information of the images. The coherence contains additional information that is useful for detecting point targets which change their location in an area of interest (AOI). In this research, a RGB colour composite image was generated with a intensity image (master image), a intensity change image as a difference between master image and slave image, and a coherence image generated as a part of SAR interferometric processing. We developed a technique performing detection of a point target movement using SAR interferometry and applied it to suitable tandem pair images of ERS-1 and ERS-2 as test data. The possibility of change detection of a point target in the AOI could be identified with the technique proposed in this research.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.496-499
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• 1995

In this paper, a new detection scheme, the detectable maneuver set (DMS) scheme, is proposed by incorporating the trade-off property between target maneuver magnitude and detection time delay. With this new detection scheme, small maneuvers can be effectively detected without enlarging window size. Simulation results show that the proposed DMS scheme gives better tracking performance.

• Food Engineering Progress
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• v.21 no.3
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• pp.191-200
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• 2017

There have been great efforts to develop a rapid and sensitive detection method to monitor the presence of pathogenic bacteria in food. While a number of methods have been reported for bacterial detection with a detection limit to a single digit, most of them are suitable only for the bacteria in pure culture or buffered solution. On the other hand, foods are composed of highly complicated matrices containing carbohydrate, fat, protein, fibers, and many other components whose composition varies from one food to the other. Furthermore, many components in food interfere with the downstream detection process, which significantly affect the sensitivity and selectivity of the detection. Therefore, isolating and concentrating the target pathogenic bacteria from food matrices are of importance to enhance the detection power of the system. The present review provides an introduction to the representative sample preparation strategies to isolate target pathogenic bacteria from food sample. We further describe the nucleic acid-based detection methods, such as PCR, real-time PCR, NASBA, RCA, LCR, and LAMP. Nucleic acid-based methods are by far the most sensitive and effective for the detection of a low number of target pathogens whose performance is greatly improved by combining with the sample preparation methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.231-238
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• 2017

Detecting small infrared targets from the low-SCR images at a long distance is very hard. The previous Local Contrast Method (LCM) algorithm based on the human visual system shows a superior performance of detecting small targets by a background suppression technique through local contrast measure. However, its slow processing speed due to the heavy multi-scale processing overhead is not suitable to a variety of real-time applications. This paper presents a lightweight real-time small target detection algorithm, called by the Improved Selective Local Contrast Method (ISLCM), to reduce the scale-invariant computational overhead. The proposed ISLCM applies the improved local contrast measure to the predicted selective region so that it may have a comparable detection performance as the previous LCM while guaranteeing low scale-invariant computational load by exploiting both adaptive scale estimation and small target feature feasibility. Experimental results show that the proposed algorithm can reduce its computational overhead considerably while maintaining its detection performance compared with the previous LCM.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1253-1258
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• 2013

This Paper deals with detection and defense methods for underwater weapons because there are so many dangers of underwater weapons not only in the war period but also in the peace time. Underwater mines are the representative strategic arms. The sensors and target detection methods, threat elimination method of mines included in this paper. Among the various sensors of mine, we use the magnetometor for target detection method in the simulation and execute the analysis of magnetic field of detected target ships. It will be also provided that effectiveness of target detection, sweeping method of mine, tactics of mine planning and mine sweeping and so on.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.746-755
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• 2013

This paper presents a three dimensional bilateral filter detecting target trajectory, extracting spatial target information using two dimensional bilateral filter and temporal target information using one dimensional bilateral filter. In order to discriminate edge pixel with flat background and target region spatially and temporally, spatial and temporal variance are used for an image and temporal profile. With this procedure, background and background profile are predicted without original target through two dimensional and one dimensional bilateral filter. Finally, using spatially predicted background and temporally predicted background profile, small target can be detected. For comparison of existing target detection methods and the proposed method, the receiver operating characteristics (ROC) is used in experimental results. Experimental results show that the proposed method has superior target detection rate and lower false alarm rate.

• The Journal of the Acoustical Society of Korea
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• v.38 no.4
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• pp.415-426
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• 2019

In this paper, we discussed automatic target tracking algorithms for diver detection sonar that observes penetration forces of coastal military installations and major infrastructures. First of all, we analyzed sea trial data in diver detection sonar and composed automatic target tracking algorithms based on track existence probability as track quality measure in clutter environment. In particular, these are presented track management algorithms which include track initiation, confirmation, termination, merging and target tracking algorithms which include single target tracking IPDAF (Integrated Probabilistic Data Association Filter) and multitarget tracking LMIPDAF (Linear Multi-target Integrated Probabilistic Data Association Filter). And we analyzed performances of automatic target tracking algorithms using sea trial data and monte carlo simulation data.