• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.3-8
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• 2006

This paper discusses current challenges, as a result of the rapid increase in air travel, and future navigation needs of Civil Aviation. The objectives pursued by ANASTASIA, a sixth framework European Commission project, are presented. The methods used in the derivation of the navigation performance requirements are introduced and discussed in the context of precision approaches. High-level impacts on the avionics receiver of integrating additional multi-frequency ranging signals from a modernized GPS and Galileo into the current navigation architecture are investigated. Expected performance achievements are presented.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.35-42
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• 2021

The position accuracy of the stand-alone Regional Navigation Satellite System (RNSS) users is more than tens of meters because of various error sources in satellite navigation signals. This paper focuses on wide-area differential (WAD) positioning technique, which is already applied in Global Navigation Satellite System (GNSS), in order to improve the position accuracy of RNSS users. According to the simulation results in the very narrow ground network in regional area, the horizontal position error of stand-alone RNSS is about RMS 11.6 m, and that of RNSS with WAD technique, named the WAD-RNSS, is about RMS 2.5 m. The accuracy performance has improved by about 78%.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.92-97
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• 2024

This paper provides a study of distributional perspective on reinforcement learning for application in mobile robot navigation. Mapless navigation algorithms based on deep reinforcement learning are proven to promising performance and high applicability. The trial-and-error simulations in virtual environments are encouraged to implement autonomous navigation due to expensive real-life interactions. Nevertheless, applying the deep reinforcement learning model in real tasks is challenging due to dissimilar data collection between virtual simulation and the physical world, leading to high-risk manners and high collision rate. In this paper, we present distributional reinforcement learning architecture for mapless navigation of mobile robot that adapt the uncertainty of environmental change. The experimental results indicate the superior performance of distributional soft actor critic compared to conventional methods.

• Journal of Positioning, Navigation, and Timing
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• v.1 no.1
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• pp.1-6
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• 2012

For a Global Positioning System (GPS) receiver, it is known that a Vector Delay Locked Loop (DLL) in which the code signals of each satellite are tracked in parallel by using navigation results shows better performance in the aspect of the tracking accuracy and the robustness than that of a Scalar DLL. However, the quantitative analysis and the logical grounds for that performance enhancement of the Vector DLL are not sufficient. This paper, therefore, proposes the structure of the GPS receiver with the Vector DLL and analyzes the performance of it. The tracking and the positioning accuracy of the Vector DLL are theoretically analyzed and confirmed by simulation results. From the simulation results, it can be seen that the tracking and positioning accuracy has been improved about 30% in case that the receiver is static and the positioning is conducted for every Pre-detection Integration Time (PIT) while C/N0 is 45 dB-Hz.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.569-577
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• 2015

The navigation algorithm developed based on the extended Kalman filter (EKF) sometimes diverges when the linearity between the measurements and the states is not preserved. In this study, new update conditions together with two conditions from previous study for gravity gradient referenced navigation (GGRN) were deduced for the filter performance. Also, the effect of each update conditions was evaluated imposing the various magnitudes of the database (DB) and the sensor errors. In case the DB and the sensor errors were supposed to 0.1 Eo and 0.01 Eo, the navigation performance was improved in the eight trajectories by using part of gravity gradient components that independently estimate states located within trust boundary. When applying only the components showing larger variation, around 200% of improvement was found. Even the DB and sensor error were supposed to 3 Eo, six update conditions improved performance in at least seven trajectories. More than five trajectories generated better results with 5 Eo error of the DB and the sensor. Especially, two update conditions successfully control divergence, and bounded the navigation error to the 1/10 level. However, these update conditions could not be generalized for all trajectories so that it is recommended to apply update conditions at the stage of planning, or as an index of precision of GGRN when combine with various types of geophysical data and algorithm.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.1
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• pp.11-16
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• 2014

A Satellite Based Augmentation System (SBAS) is a representative differential GNSS system, which is used for the navigation performance improvement of Global Navigation Satellite System (GNSS) users. SBAS has been developed focusing on the securement of user integrity so that it can be used for the navigation in aviation fields. Accordingly, the development of SBAS has been completed, and it has been actively used in the United States, Europe, and Japan. As the new satellite of Global Positioning System (GPS) recently started to broadcast new civil signals (L5 frequency), the methods for improving user navigation performance in SBAS using this signal have also been studied. In Korea, to keep pace with these circumstances, full-scale SBAS development is expected to start in 2014, and studies on dual-frequency SBAS using L1/L5 frequencies will also be performed. In this study, before the full-scale development of dual-frequency SBAS in Korea, a simulation was performed to predict the performance and analyze the expected effects.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.2
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• pp.53-57
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• 2017

eLoran refers to a terrestrial navigation system using high-power low-frequency signals. Thus, it can be regarded as a positioning, navigation and timing (PNT) system to back up a global navigation satellite system (GNSS) or an alternative to GNSS. South Korea is vulnerable to interference such as GNSS jamming in particular. Therefore, South Korea has made an effort to develop an independent navigation system through eLoran system. More particularly, an eLoran testbed has been developed to be used in the northwest sea area and research on applicability of eLoran in South Korea has been underway. The present study analyzes expected performance of eLoran according to locations of newly built eLoran transmitting stations as part of the eLoran testbed research. The performance of eLoran is analyzed in terms of horizontal position accuracy, and horizontal dilution of precision (HDOP) information was used since it affects accuracy significantly. The target service areas of the eLoran testbed are Incheon and Pyeongtaek Ports, and the required target performance is positioning accuracy of 20 m position within 30 km coverage of the target service area.

• Journal of Advanced Navigation Technology
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• v.16 no.5
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• pp.738-743
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• 2012

Kalman filter is generally used in INS/GPS integrated navigation filter. However, the INS with low performance inertia sensor can not find accurate azimuth in initial alignment stage because sensor noise level is too large compare to Earth rotation rate, therefore the performance and stability of Kalman filter can not be guaranteed. In this paper, the extended Kalman filter and particle filter combined filter structure which can be overcome large initial azimuth error is proposed.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.369-378
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• 2013

This paper presents a vision/LiDAR integrated navigation system that provides accurate relative navigation performance on a general ground surface, in GNSS-denied environments. The considered ground surface during flight is approximated as a piecewise continuous model, with flat and slope surface profiles. In its implementation, the presented system consists of a strapdown IMU, and an aided sensor block, consisting of a vision sensor and a LiDAR on a stabilized gimbal platform. Thus, two-dimensional optical flow vectors from the vision sensor, and range information from LiDAR to ground are used to overcome the performance limit of the tactical grade inertial navigation solution without GNSS signal. In filter realization, the INS error model is employed, with measurement vectors containing two-dimensional velocity errors, and one differenced altitude in the navigation frame. In computing the altitude difference, the ground slope angle is estimated in a novel way, through two bisectional LiDAR signals, with a practical assumption representing a general ground profile. Finally, the overall integrated system is implemented, based on the extended Kalman filter framework, and the performance is demonstrated through a simulation study, with an aircraft flight trajectory scenario.

• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.367-373
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• 2016

This paper describes the development of a navigation HILS (hardware in the loop simulation) system for an integrated navigation performance analysis of a large diameter unmanned underwater vehicle (LDUUV). The HILS system was used for the performance analysis of the LDUUV. When a conventional HILS system is used, it is not possible to calculate the velocity and position using an inertial navigation system (INS). To cope with this problem, an external acceleration was generated. To evaluate the proposed method, we compare the results of a Monte Carlo simulation and navigation HILS experiment.