• Journal of Advanced Navigation Technology
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• v.8 no.2
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• pp.120-128
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• 2004

Although conventional OFDM/QAM modulation scheme using guard interval is robust to channel induced ISI (Inter-Symbol Interference) in time-domain, it is very sensitive to ICI (Inter-Carrier Interference) due to doppler effect in frequency domain. OFDM/OQAM-IOTA modulation scheme utilizes IOTA (Isotropic Orthogonal Transform Algorithm) filter that has orthogonality in time and frequency domain so that it is robust to delay spread and doppler effect. OFDM/OQAM-IOTA system can increase bandwidth effeciency since it does not use guard interval. In this paper, we show the structure of OFDM/OQAM-IOTA and perfect channel estimation scheme for OFDM/OQAM-IOTA system. We also compare OFDM/OQAM-IOTA system and OFDM/QAM system in AWGN and 1-path Rayleigh fading channel. Simulation results show that OFDM/OQAM system outperforms OFDM/QAM system.

• Journal of Advanced Navigation Technology
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• v.19 no.2
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• pp.116-122
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• 2015

Motivated by continuous increase in flight demand, awareness of the importance in developing ways to increase aircraft operational efficiency on the airport movement area has been raised. This paper proposes a new routing algorithm for providing the shortest path in a right time, enhancing the aircraft movement efficiency. Many researches on developing algorithms have been performed, for example, Dijkstra algorithm and $A^*$ algorithm. The Dijkstra algorithm provide optimal solution but could possibly provide it with a cost of relatively longer computation time. On the other hand, $A^*$ algorithm does not guarantee the optimality of a solution. In this paper, we suggest a Hybrid $A^*$ algorithm, incorporating both algorithms to eliminate the weaknesses. Rigorous test shows the proposed Hybrid $A^*$ algorithm may achieve shorter computing time and optimality in searching the shortest path.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.72-77
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• 2022

Among the techniques of reinforcement learning, Q-Learning means learning optimal policies by learning Q functions that perform actionsin a given state and predict future efficient expectations. Q-Learning is widely used as a basic algorithm for reinforcement learning. In this paper, we studied the effectiveness of selecting and learning efficient paths by designing policies and rewards based on Q-Learning. In addition, the results of the existing algorithm and punishment compensation policy and the proposed punishment reinforcement policy were compared by applying the same number of times of learning to the 8x8 grid environment of the Frozen Lake game. Through this comparison, it was analyzed that the Q-Learning punishment reinforcement policy proposed in this paper can significantly increase the learning speed compared to the application of conventional algorithms.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.132-133
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• 2023

The safe evacuation of people during disasters is of utmost importance. Various life safety evacuation simulation tools have been developed and implemented, with most relying on algorithms that analyze maps to extract the shortest path and guide agents along predetermined routes. While effective in predicting evacuation routes in stable disaster conditions and short timeframes, this approach falls short in dynamic situations where disaster scenarios constantly change. Existing algorithms struggle to respond to such scenarios, prompting the need for a more adaptive evacuation route algorithm that can respond to changing disasters. Artificial intelligence technology based on reinforcement learning holds the potential to develop such an algorithm. As a fundamental step in algorithm development, this study aims to evaluate whether an evacuation algorithm developed by reinforcement learning satisfies the performance conditions of the evacuation simulation tool required by IMO MSC.1/Circ1533.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.59-60
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• 2023

The automation of container terminals is an important factor that determines port competitiveness, and global advanced ports tend to strengthen their competitiveness through container terminal automation. The operational efficiency of the AGV, which is an essential transport equipment of the automated terminal, can improve the productivity of the automated terminal. The operation of AGVs in automated container terminals differs from that of conventional container terminals, as it is based on an automated system in which AGVs travel along designated paths and operate according to assigned tasks, requiring consideration of factors such as workload, congestion, and collisions. To prevent such problems and improve the efficiency of AGV operations, a more sophisticated model is necessary. Thus, this paper proposes an AGV scheduling model that takes into account the AGV travel path and task assignment within the terminal The model prevent the problem of deadlock and. various cases are generated by changing AGV algebra and number of tasks to create AGV driving situations and evaluate the proposed algorithm through algorithm and optimization analysis.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.487-495
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• 2022

This paper describes the design and development of a high-power transmit receive module(TRM) for mounting on X-band synthetic aperture radar(SAR) of the NEXTSat-2. The TRM generates a high-power pulse signal with a bandwidth of 100 MHz in the target frequency range of X-band and amplifies a low-noise on the received signal. Tx. path of the TRM has output signal level of more than 200 watts (53.01 dB), pulse droop of 0.35 dB, signal strength change of 0.04 dB during transmission signal output, and phase change of 1.7 ˚. Rx. path has noise figure of 3.99 dB and gain of 37.38 ~ 37.46 dB. It was confirmed the TRM satisfies all requirements. The TRM mounted on the NEXTSat-2 flight model(FM) which will be launched using the KSLV-II (Nuri).

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.193-200
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• 2024

This paper describes the design and development of a transmit receiver module(TRM) for mounting on X-band SAR of the NEXTSat-2. The TRM generates the chirp signal with required bandwidth through the DDS in X-band and performs frequency conversion, combination for the signal to transmit and be received and frequency synthesis. Tx path of the TRM produces signals of total 28 bandwidths up to 96.8 MHz and has output signal level of more than + 9.37 dBm. Rx path of the TRM has minimum noise figure of 15.7 dB. The measurement results show that required requirements are satisfied. The TRM is installed on the NEXTSat-2 flight model(FM), launched by KSLV-II(Nuri) on May 23, 2023 and currently operational.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2367-2372
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• 2009

Recently, Many studies have been progressing to path-finding adapted dynamic information on the Terminal Based Navigation System(TBNS). The algorithms proposed are based on $A^*$ algorithm. Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost. Path-finding with an abstract graph which expresses real road network as a simple graph is proposed for reducing dependency of heuristic and exploring cost. In this paper, two abstract graph that are different method of construction, Homogeneous Node merging($AG^H$) and Connected Node Merging($AG^C$), are implemented. In result of evaluation of performance, $AG^C$ has better performance than $AG^H$ at construction cost and the number of node access but $AG^C$ has worse performance than AGH at exploring cost.

• Spatial Information Research
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• v.19 no.3
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• pp.43-52
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• 2011

Recently, interest in location-based service (LBS) which utilizes a DBMS in mobile system environment has been increasing, and it is expected to overcome the existing file-based system's limitation in advanced in-vehicle system by utilizing DBMS's advantages such as efficient storage, transaction management, modelling and spatial queries etc. In particular, the road network data corresponds to the most essential domain in a route planning system, which needs efficient management and maintenance. Accordingly, this study aims to develop an efficient graph-based geodata model for topological network data and to support dynamic path computation algorithm based on heuristic approach in mobile LBS system. To achieve this goal, we design a data model for supporting the hierarchy of network, and implement a path planning system to evaluate its performance in mobile LBS system. Last but not least, we find out that the designed path computation algorithm with hierarchical graph model reduced the number of nodes used for finding and improved the efficiency of memory.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1483-1492
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• 1996

In this paper, related on the postal business with the GIS(Geographics Information System), it discusses design and implementation of the PROS(Postal Route Optimization System) model and its main module, the shortest path generation algorithm, for supporting to postal route managements. It explains examples requirements of postal route system, and suggests the efficient PROS model using our developed shortest path generation algorithm. Because the shortest path algorithm adopts not only consider the Dijkstra algorithm of graph theory, but also the method with the direction property, PROS can be implemented with fast and efficient route search. PROS is mainly constituted of the Shortest Generator, the Isochronal Area Generator, and the Path Rearrangement Generator. It also exploits the GIS engine and the spatial DBMS (Data Base Management System) for processing coordinates in the map and geographical features. PROS can be used in the management of postal delivery business and delivery area and route, and in the rearrangement of route. In the near future, it can be also applied to commercial delivery businesses, guides of routs and traffic informations, and auto navigation system with GPS(Global Positioning System).