• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.429-435
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• 2012

Although GNSS hardware and software technologies have been steadily advanced, it is still difficult to obtain reliable positioning results in the area with lots of signal blockage. In this study, algorithms for integrated GPS and GLONASS double difference relative positioning were developed and its performance was validated via simulations of signal blockages. We assumed that signal blockages are caused by high-rise buildings to the east, west, and south directions. And then, GPS-only and integrated GPS/GLONASS positioning accuracy was analysed in terms of 2-dimensional positioning accuracies. Compared with GPS-only positioning, the positioning accuracy of integrated GPS/GLONASS improved by 0.3-13.5 meters.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.3-8
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• 2006

The next decade promises drastic improvements and additions to global navigation satellite systems (GNSS). Plans for GPS modernization include a civilian code measurement on the L2 frequency and a new L5 signal at 1176.45 MHz. Current speculations indicate that a fully operational constellation with these improvements could be available by 2013. Simultaneously, the Galileo Joint Undertaking is in the development and validation stages of introducing a parallel GNSS called Galileo. Galileo will also transmit freely available satellite navigation signals on three frequencies and is scheduled to be fully operational as early as 2008. In other words, a dual system receiver (e.g., GPS+GALILEO) for general users can access six civil frequencies transmitted by at least fifty eights navigation satellites in space. The advent of GALILEO and the modernization of GPS raise a lot of attention to the study of the compatibility and interoperability of the two systems. A number of performance analyses have been conducted in a global scale with respect to availability, reliability, accuracy and integrity in different simulated scenarios (such as open sky and urban canyons) for the two systems individually and when integrated. Therefore, the scope of this article aims at providing the technical benefits analysis for Taiwan specifically in terms of the performance indices mentioned above in a local scale, especially in typical urban canyon scenarios. The conclusions gained by this study will be applied by the Land Survey Bureau of Taiwanese as the guideline for developing future GNSS tracking facilities and dual GNSS processing module for precise surveying applications in static and kinematic modes.

• Atmosphere
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• v.31 no.3
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• pp.251-265
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• 2021

This study examined the impact of assimilating the bending angle (BA) obtained via the global navigation satellite system radio occultation (GNSS RO) of the three new satellites (KOMPSAT-5, FY-3C, and FY-3D) on analyses and forecasts of a numerical weather prediction model. Numerical data assimilation experiments were performed using a three-dimensional variational data assimilation system in the Korean Integrated Model (KIM) at a 25-km horizontal resolution for August 2019. Three experiments were designed to select the height and quality control thresholds using the data. A comparison of the data with an analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) integrated forecast system showed a clear positive impact of BA assimilation in the Southern Hemisphere tropospheric temperature and stratospheric wind compared with that without the assimilation of the three new satellites. The impact of new data in the upper atmosphere was compared with observations using the infrared atmospheric sounding interferometer (IASI). Overall, high volume GNSS RO data helps reduce the RMSE quantitatively in analytical and predictive fields. The analysis and forecasting performance of the upper temperature and wind were improved in the Southern and Northern Hemispheres.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.599-606
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• 2014

Since the accuracy of Global Positioning System (GPS)-based vehicle positioning system is significantly degraded or does not work appropriately in the urban canyon, the integration techniques of GPS with Inertial Navigation System (INS) have intensively been developed to improve the continuity and reliability of positioning. However, its accuracy is degraded as INS errors are not properly corrected due to the GPS signal blockage. Recently, the image-based positioning techniques have been started to apply for the vehicle positioning for the advanced in processing techniques as well as the increased the number of cars installing the camera. In this study, Single Photo Resection (SPR), which calculates the camera exterior orientation parameters using the Ground Control Points (GCPs,) has been integrated with the INS/GPS for continuous and stable positioning. The INS/GPS/SPR integration was implemented in both of a loosely and a tightly coupled modes, based on the Extended Kalman Filter (EKF). In order to analyze the performance of INS/SPR integration during the GPS outage, the simulation tests were conducted with a consideration of factors affecting SPR performance. The results demonstrate that the accuracy of INS/SPR integration is depended on magnitudes of the GCP errors and SPR processing intervals. Additionally, the simulation results suggest some required conditions to achieve accurate and continuous positioning, used the INS/SPR integration.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.5
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• pp.590-598
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• 2019

Aerial photographs taken by an image sensor fixed on a flight body, e.g. without a gimbal, are generally distorted according to its attitude, altitude and angle of view in flight. This can result in a significant difficulty of analyzing geometric information which should be integrated for numerous still frames. In this study, a simulation method of observation performance that uses geometric relationships between navigation data and image data is suggested, and this method is shown to be very useful for easily examining the integrated information such as the total range of photography, the time of target acquisition, etc.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.635-642
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• 2023

With the development of artificial intelligence technology, drones are evolving beyond simple remote control tools into intelligent drones that perform missions autonomously. The importance of drones is gradually gaining attention due to the use of drones in overseas military conflicts and the analysis of the future operational environment in Korea. AMAD is proposed for the rapid development of intelligent drones. In order to develop intelligent software based on AMAD, an integrated development environment (IDE) that supports users with functions such as debugging, performance evaluation, and monitoring is essential. In this paper, we define the concepts of the development environment required for intelligent software development and describe the results of reflecting them in the design of the IDE and AMAD's agents, SVI and MPD, which are interfaced with the IDE.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1092-1098
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• 2007

A mobile robot localization problem can be classified into following three sub-problems as an observation likelihood model, a motion model and a filtering technique. So far, we have developed the range sensor based, integrated localization scheme, which can be used in human-coexisting real environment such as a science museum and office buildings. From those experiences, we found out that there are several significant issues to be solved. In this paper, we focus on three key issues, and then illustrate our solutions to the presented problems. Three issues are listed as follows: (1) Investigation of design requirements of a desirable observation likelihood model, and performance analysis of our design (2) Performance evaluation of the localization result by computing the matching error (3) The semi-global localization scheme to deal with localization failure due to abrupt wheel slippage In this paper, we show the significance of each concept, developed solutions and the experimental results. Experiments were carried out in a typical modern building environment, and the results clearly show that the proposed solutions are useful to develop practical and integrated localization schemes.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.173-183
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• 2017

This paper proposes an integrated positioning system to localize a moving object in the shadow-area that exists in the water tank. The new water tank for underwater robots is constructed to evaluate the navigation performance of underwater vehicles. Several sensors are integrated in the water tank to provide the position information of the underwater vehicles. However there are some areas where the vehicle localization becomes very poor since the very limited sensors such as sonar and depth sensors are effective in underwater environment. Also there are many disturbances at sonar data. To reduce these disturbances, an extended Kalman filter has been adopted in this research. To localize the underwater vehicles under the hostile situations, a SVR (Support Vector Regression) has been systematically applied for estimating the position stochastically. To demonstrate the performance of the proposed algorithm (an extended Kalman filter + SVR analysis), a new UI (User Interface) has been developed.

• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.402-412
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• 2017

The convergence of broadcasting and telecommunication technologies is a key issue of the ubiquitous networks. So this paper offers the convergence of integrated telecommunication networks and broadcasting system, Advanced Terrestrial Digital Multimedia Broadcasting (AT-DMB), and the interconnection of them via the Media Independent Information Server/Service (MIIS). Then, this paper proposes the fast wakeup and connection mechanism with concepts for improving QoS and energy efficiency simultaneously. In the proposed convergence network, our mechanism places the key on the minimization of both the incoming service delay destined to a turned-off interface by using the broadcasting network and the additional energy consumption. This paper further evaluates the performance of proposed mechanism through the numerical and experimental analysis and has confirmed the decrease of both service delay and energy consumption.