• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.1-14
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• 2023

Underwater images carry information that is useful in the fields of aquaculture, underwater military security, navigation, transportation, and so on. In this research, we transmitted an underwater image through various underwater mediums in the presence of underwater turbulence and beam attenuation effects using a high-speed visible optical carrier signal. The optical beam undergoes scintillation because of the turbulence and attenuation effects; therefore, distorted images were observed at the receiver end. To understand the behavior of the communication media, we obtained the bit error rate (BER) performance of the system with respect to the average signal-to-noise ratio (SNR). Also, the structural similarity index (SSI) and peak SNR (PSNR) metrics of the received image were evaluated. Based on the received images, we employed suitable nonlinear filters to recover the distorted images and enhance them further. The BER, SSI, and PSNR metrics of the specific nonlinear filters were also evaluated and compared with the unfiltered metrics. These metrics were evaluated using the on-off keying and binary phase-shift keying modulation techniques for the 50-m and 100-m links for beam attenuation resulting from pure seawater, clear ocean water, and coastal ocean water mediums.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.927-934
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• 2012

In this paper, we present relative positioning algorithm for moving land vehicle using GPS, MEMS IMU and B-CDMA module. This algorithm does not calculate precise absolute position but calculates relative position directly, so additional infrastructure and I2V communication device are not required. Proposed algorithm has several steps. Firstly, unbiased relative position is calculated using pseudorange difference between two vehicles. Simultaneously, the algorithm estimates position of each vehicle using GPS/INS integration. Secondly, proposed algorithm performs filtering and finally estimates relative position and relative velocity. Using proposed algorithm, we can obtain more precise relative position for moving land vehicles with short time interval as IMU sensor has. The simulation is performed to evaluate this algorithm and the several field tests are performed with real time program and miniature vehicles for verifying performance of proposed algorithm.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.43-49
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• 2017

Generally, loop filter based scalar tracking loops (LF-STL) have been used for global positioning system (GPS) signal tracking algorithm. This paper introduces the accuracy and robustness of linear-quadratic-Gaussian based vector tracking loop (LQG-VTL) algorithm instead of LF-STL. To verify the accuracy of LQG-VTL, we confirm that the measurements estimation errors of the LQG based scalar tracking loops (LQG-STL) are improved by more than 60 % compared to LF-STL. Also, when LQG-VTL is used, measurements estimation errors decrease compared to LQG-STL, and position/velocity estimation errors also decrease as the number of satellites increases. To verify the robustness of LQG-VTL, we confirm that LQG-VTL can estimate position/velocity and measurements successively compared to LF-STL in temporal signal attenuation of 30 dB-Hz during 4 seconds.

• Journal of Advanced Navigation Technology
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• v.15 no.2
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• pp.287-297
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• 2011

As electronic mails are being widely used for facility and speedness of information communication, as the amount of spam mails which have malice and advertisement increase and cause lots of social and economic problem. A number of approaches have been proposed to alleviate the impact of spam. These approaches can be categorized into pre-acceptance and post-acceptance methods. Post-acceptance methods include bayesian filters, collaborative filtering and e-mail prioritization which are based on words or sentances. But, spammers are changing those characteristics and sending to avoid filtering system. In the case of Korean, the abnormal usages can be much more than other languages because syllable is composed of chosung, jungsung, and jongsung. Existing formal expressions and learning algorithms have the limits to meet with those changes promptly and efficiently. So, we present an methods for recognizing Korean abnormal language(Koral) to improve accuracy and efficiency of filtering system. The method is based on syllabic than word and Smith-waterman algorithm. Through the experiment on filter keyword and e-mail extracted from mail server, we confirmed that Koral is recognized exactly according to similarity level. The required time and space costs are within the permitted limit.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.609-617
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• 2016

In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.135-143
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• 2009

Integrating the Global Positioning System (GPS) and Inertial Navigation System (INS) sensor technologies using the precise GPS Carrier phase measurements is a methodology that has been widely applied in those application fields requiring accurate and reliable positioning and attitude determination; ranging from 'kinematic geodesy', to mobile mapping and imaging, to precise navigation. However, such integrated system may not fulfil the demanding performance requirements when the baseline length between reference and mobil user GPS receiver is grater than a few tens of kilometers. This is because their positioning/attitude determination is still very dependent on the errors of the GPS observations, so-called "baseline dependent errors". This limitation can be remedied by the integration of GPS and INS sensors, using multiple reference stations. Hence, in order to derive the GPS distance dependent errors, this research proposes measurement processing algorithms for multiple reference stations, such as a reference station ambiguity resolution procedure using linear combination techniques, a error estimation based on Kalman filter and a error interpolation. In addition, all the algorithms are evaluated by processing real observations and results are summarized in this paper.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.9
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• pp.781-788
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• 2016

In this paper, a real-time on-board orbit determination algorithm using the high precise orbit propagator is suggested and its performance is analyzed. Orbit determination algorithm is designed with the Extended Kalman Filter. And it utilizes the orbit calculated from the Pseudo-range as observed data. The performance of the on-board orbit determination method implemented in the GPS-12 receiver is demonstrated using the GNSS simulator. Orbit determination performance using high precise orbit propagator was analyzed in comparison to the orbit determination result using $J_2$ orbit propagator. The analysis result showed that position and velocity error are improved from 43.61 m($3{\sigma}$) to 23.86 m($3{\sigma}$) and from 0.159 m/s($3{\sigma}$) to 0.044 m/s($3{\sigma}$) respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.352-361
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• 2021

An underwater positioning method that can be applied to structures for underwater construction is being developed at the Korea Institute of Ocean Science and Technology. The method uses an extended Kalman filter (EKF) based on an inertial navigation system for precise and continuous position estimation. The observation matrix was configured to be variable in order to apply asynchronous measured sensor data in the correction step of the EKF. A Doppler velocity logger (DVL) can acquire signals only when attached to the bottom of an underwater structure, and it is difficult to install and recover. Therefore, a complex sensor device for underwater structure attachment was developed without a DVL in consideration of an underwater construction environment, installation location, system operation convenience, etc.. Its performance was verified through a water tank test. The results are the measured underwater position using an ultra-short baseline, the estimated position using only a position vector, and the estimated position using position/velocity vectors. The results were compared and evaluated using the circular error probability (CEP). As a result, the CEP of the USBL alone was 0.02 m, the CEP of the position estimation with only the position vector corrected was 3.76 m, and the CEP of the position estimation with the position and velocity vectors corrected was 0.06 m. Through this research, it was confirmed that stable underwater positioning can be carried out using asynchronous sensors without a DVL.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.667-675
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• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.11-19
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• 2014

In recent SONAR (sound navigation and ranging) systems, wideband active SONAR systems has received more attention than narrowband SONAR systems due to the remarkable detection performance in terms of range resolution. However, the wideband SONAR systems usually requires a huge amount of computational burden in order to achieve their own superiority. To cope with this drawback of the wideband SONAR systems, this paper proposes a fast target detection and velocity estimation method using an extended replica in wideband hyperbolic frequency modulation active SONAR system. Computer simulation shows that the proposed method can be implemented by a highly reduced computational complexity with a little performance degradation in target detection and velocity estimation compared to the conventional filter bank method.