• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1946-1956
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• 2001

In this paper, we propose a novel 2-D partial matching algorithm based on model-based stochastic analysis of feature correspondences in a relation vector space, which is quite robust to shape variations as well as invariant to geometric transformations. We represent an object using the ARG (Attributed Relational Graph) model with features of a set of relation vectors. In addition, we statistically model the partial occlusion or noise as the distortion of the relation vector distribution in the relation vector space. Our partial matching algorithm consists of two-phases. First, a finite number of candidate sets areselected by using logical constraint embedding local and structural consistency Second, the feature loss detection is done iteratively by error detection and voting scheme thorough the error analysis of relation vector space. Experimental results on real images demonstrate that the proposed algorithm is quite robust to noise and localize target objects correctly even inseverely noisy and occluded scenes.

• Journal of Astronomy and Space Sciences
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• v.22 no.4
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• pp.385-392
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• 2005

We developed an algorithm to efficiently detect streaks in survey images and made a performance test with YSTAR-NEOPAT images obtained by the 0.5m telescope stationed in South Africa. Fast moving objects whose apparent speeds exceed 10 arcsec/min are the main target of our algorithm; these include artificial satellites, space debris, and very fast Near-Earth Objects. Our algorithm, based on the outline shape of elongated sources employs a step of image subtraction in order to reduce the confusion caused by dense distribution of faint stars. It takes less than a second to find and characterize streaks present in normal astronomical images of 2K format. Comparison with visual inspection proves the efficiency and completeness of our automated detection algorithm. When applied to about 7,000 time-series images from YSTAR telescope, nearly 700 incidents of streaks are detected. Fast moving objects are identified by the presence of matching streaks in adjoining frames. Nearly all of confirmed fast moving objects turn out to be artificial satellites or space debris. Majority of streaks are however meteors and cosmic ray hits, whose identity is often difficult to classify.

• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.23-39
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• 2019

The use of drone-bots is demanded in times regarding the reduction of military force, the spread of the life-oriented thought, and the use of innovative technology in the defense through the fourth industrial revolution. Especially, the drone's surveillance and reconnaissance are expected to play a big role in the future battlefield. However, there are not many cases in which the concept of operation is studied scientifically. In this study, We propose search algorithms for reconnaissance drone through simulation analysis. In the simulation, the drone and target move linearly in continuous space, and the target is moving adopting the Random-walk concept to reflect the uncertainty of the battlefield. The research investigates the effectiveness of existing search methods such as Parallel and Spiral Search. We analyze the probabilistic analysis for detector radius and the speed on the detection probability. In particular, the new detection algorithms those can be used when an enemy moves toward a specific goal, PS (Probability Search) and HS (Hamiltonian Search), are introduced. The results of this study will have applicability on planning the path for the reconnaissance operations using drone-bots.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.3
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• pp.362-370
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• 2011

This paper presents a K-band radar system installed on the ground moving vehicle to detect and track a high-speed target. The presented radar is separated into three search regions to satisfy a wide area detection and a limitation of the installing space of the radar, and each region performs detecting the target independently and tracking the detected target automatically. The presented radar radiating K-band FMCW waveform acquires range and velocity information of the target at the every dwell and receiving antenna of the radar is applied the multiple baseline interferometer to extract the precise angle information of the target. 3-dimensional tracking accuracy of the radar is 0.25 m RMSE measured actually through a fire experiment of an imitation target.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.5 s.335
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• pp.55-62
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• 2005

In this paper, we propose an efficient symbol detection algorithm for space-frequency OFDM (SF-OFDM) transmit diversity scheme and present the implementation results of the SF-OFDM WLAN baseband processor with the proposed algorithm. When the number of sub-carriers in SF-OFDM scheme is small, the interference between adjacent sub-carriers may be generated. The proposed algorithm eliminates this interference in a parallel manner and obtains a considerable performance improvement over the conventional detection algorithm. The bit error rate (BER) performance of the proposed detection algorithm is evaluated by the simulation. In the case of 2 transmit and 2 receive antennas, at $BER=10^{-4}$ the proposed algorithm obtains about 3 dB gain over the conventional detection algorithm. The packet error rate (PER), link throughput, and coverage performance of the SF-OFDM WLAN with the proposed detection algorithm are also estimated. For the target throughput at $80\%$ of the peak data rate, the SF-OFDM WLAN achieves the average SNR gain of about 5.95 dB and the average coverage gain of 3.98 meter. The SF-OFDM WLAN baseband processor with the proposed algorithm was designed in a hardware description language and synthesized to gate-level circuits using 0.18um 1.8V CMOS standard cell library. With the division-free architecture, the total logic gate count for the processor is 945K. The real-time operation is verified and evaluated using a FPGA test system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.12
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• pp.865-873
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• 2019

To improve the survivability of a missile, it needs to be lowered that the detection possibility by radars on the ground. The radar exposure of the target is given as a function of relative distance from the radar to the target and RCS (Radar Cross Section). The RCS of the missile is determined by the incidence angle of the target to electromagnetic radiation emitted from the radar. Under the assumption that the missile equips appropriate attitude control system, the attitude of the missile to minimize radar exposure at a high altitude is investigated in this paper. Two different types of performance cost are considered: the total sum of RCS and the total sum of SNR during the flight. Optimal solutions against multiple ground radars are found by using a SQP (Sequential Quadratic Programming)-based optimization technique.

• Journal of Ocean Engineering and Technology
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• v.20 no.1 s.68
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• pp.69-76
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• 2006

The design of efficient search path to maximize the Cumulative Detection Probability(CDP) is mainly dependent on experience and intuition when searcher detect the target using SONAR in the ocean. Recently with the advance of modeling and simulation method, it has been possible to access the optimization problems more systematically. In this paper, a method for the optimal search path calculation is developed based on the combination of the genetic algorithm and the calculation algorithm for detection range. We consider the discrete system for search path, space, and time, and use the movement direction of the SONAR for the gene of the genetic algorithm. The developed algorithm, OASPP(Optimal Acoustic Search Path Planning), is shown to be effective, via a simulation, finding the optimal search path for the case when the intuitive solution exists. Also, OASPP is compared with other algorithms for the measure of efficiency to maximize CDP.

• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.445-452
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• 2007

We proposed a detection scheme of weather information in CCTV video images in this paper. The scheme obtains the RGB distribution of shiny day and divide a target image into cloud, rain, snow and for RGB distributions. shiny day RGB distribution. Our scheme designed systematically to detection and separation special characteristics of images from complex weather information. Our algorithm has less overhead than the previous methods to use weather database DB at the view of time and space. And our algorithm can be use in real world system with low cost of implementation. Also, our algorithm use informations of temperature, humidity, date, and time to detect the information of weather with high quality.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.48.1-48.1
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• 2009

In recent years, many candidates for extra-solar planet have been discovered from various measurement techniques. Fueled by such discoveries, new space missions for direct detection of earth-like planets have been proposed and actively studied. TPF instrument is a fair example of such scientific endeavors. One of the many technical problems that space missions such as TPF would need to solve is deconvolution of the collapsed (i.e. spatially and temporally) spectral signal arriving at the detector surface and the deconvolution computation may fall into a local minimum solution, instead of the global minimum solution, in the optimization process, yielding mis-interpretation of the spectral signal from the potential earth-like planets. To this extend, observational and theoretical understanding on the spectral bio-signal from the Earth serves as the key reference datum for the accurate interpretation of the planetary bio-signatures from other star systems. In this study, we present ray tracing computational model for the on-going simulation study on the Earth bio-signatures. A multi-layered atmospheric model and sea ice variation model were added to the existing target Earth model and a hypothetical space instrument (called AmonRa) observed the spectral bio-signals of the model Earth from the L1 halo orbit. The resulting spectrums of the Earth show well known "red-edge" spectrums as well as key molecular absorption lines important to harbor life forms. The model details, computational process and the resulting bio-signatures are presented together with implications to the future study direction.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.41.1-41.1
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• 2018

We introduce a current status and future plans of Korea Microlensing Telescope Network (KMTNet) microlensing experiments, which include an observational strategy, pipeline, event-finder, and collaborations with Spitzer. The KMTNet experiments were initiated in 2015. From 2016, KMTNet observes 27 fields including 6 main fields and 21 subfields. In 2017, we have finished the DIA photometry for all 2016 and 2017 data. Thus, it is possible to do a real-time DIA photometry from 2018. The DIA photometric data is used for finding events from the KMTNet event-finder. The KMTNet event-finder has been improved relative to the previous version, which already found 857 events in 4 main fields of 2015. We have applied the improved version to all 2016 data. As a result, we find that 2597 events are found, and out of them, 265 are found in KMTNet-K2C9 overlapping fields. For increasing the detection efficiency of event-finder, we are working on filtering false events out by machine-learning method. In 2018, we plan to measure event detection efficiency of KMTNet by injecting fake events into the pipeline near the image level. Thanks to high-cadence observations, KMTNet found fruitful interesting events including exoplanets and brown dwarfs, which were not found by other groups. Masses of such exoplanets and brown dwarfs are measured from collaborations with Spitzer and other groups. Especially, KMTNet has been closely cooperating with Spitzer from 2015. Thus, KMTNet observes Spitzer fields. As a result, we could measure the microlens parallaxes for many events. Also, the automated KMTNet PySIS pipeline was developed before the 2017 Spitzer season and it played a very important role in selecting the Spitzer target. For the 2018 Spitzer season, we will improve the PySIS pipeline to obtain better photometric results.