• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.262-271
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• 2024

In this paper, by applying deep learning, one of the A.I. techniques, through angle information, which is optical observation data generated when observing satellites at observatories, distance information from observatories is learned to predict range data, thereby increasing the precision of satellite's orbit determination. To this end, we generated observational data from GMAT, reduced the learning data error of deep learning through preprocessing of the generated observational data, and conducted deep learning through MATLAB. Based on the predicted distance information from learning, trajectory determination was performed using an extended Kalman filter, one of the filtering techniques for trajectory determination, through GMAT. The reliability of the model was verified by comparing and analyzing the orbital determination with angular information without distance information and the orbital determination result with predicted distance information from the model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.73-82
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• 2010

TERCOM(TERrain COntour Matching), which is the one of the Terrain Referenced Navigation and used in the cruise missile navigation system, is still under development. In this study, the TERCOM based on area-based matching algorithm and extended Kalman filter is analysed through simulation. In area-based matching, the mean square difference (MSD) and cross-correlation matching algorithms are applied. The simulation supposes that the barometric altimeter, radar altimeter and SRTM DTM loaded on board. Also, it navigates along the square track for 545 seconds with the velocity of 1000km per hour. The MSD and cross-correlation matching algorithms show the standard deviation of position error of 99.6m and 34.3m, respectively. The correlation matching algorithm is appeared to be less sensitive than the MSD algorithm to the topographic undulation and the position accuracy of the both algorithms is extremely depends on the terrain. Therefore, it is necessary to develop an algorithm that is more sensitive to less terrain undulation for reliable terrain referenced navigation. Furthermore, studies on the determination of proper matching window size in long-term flight and the determination of the best terrain database resolution needed by the flight velocity and area should be conducted.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.1
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• pp.63-73
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• 2014

Recently, researches on DBRN(DataBase Referenced Navigation) system are being carried out to replace GNSS(Global Navigation Satellite System), as weaknesses of GNSS were found that are caused by the intentional interference and the jamming of the satellite signal. This paper describes the gravity gradient modeling and the construction of EKF(Extended Kalman Filter) based GGRN(Gravity Gradient Referenced Navigation). To analyze the performance of GGRN, fourteen flight trajectories were made for simulations over whole South Korea. During the simulations, we considered the errors in both DB(DataBase) and sensor as well as the flight altitudes. Accurate performances were found, when errors in the DB and the sensor are small and they located at lower altitude. For comparative evaluation, the traditional TRN(Terrain Referenced Navigation) was also developed and performances were analyzed relative to those from the GGRN. In fact, most of GGRN performed better in low altitude, but both of precise gravity gradient DB and gradiometer were required to obtain similar level of precisions at the high altitude. In the future, additional tests and evaluations on the GGRN need to be performed to investigate on more factors such as DB resolution, flight speed, and the update rate.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.12
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• pp.1032-1039
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• 2012

The present paper deals with precise relative positioning of formation satellites with long baseline in low Earth orbit making use of L1/L2 dual frequency GPS carrier phase measurements. Kinematic approach means to describe the motion of objects without taking its mass/dynamics model into consideration. The advantage of the kinematic approach is that information about dynamics of the system is not applied, which gives more flexibility and could improve the scientific interest of the observations made by the mission. The ionosphere terms, which are not canceled by double differenced measurement equation in the case of the long baseline, are explicitly estimated as unknown parameters by extended Kalman filter. The estimated float ambiguities by EKF are solved by existing efficient integer vector search strategy under integer least square condition. For the integer vector search, we employ well known MLAMBDA. Finally, The feasibility and accuracy of processing scheme are demonstrated using the GPS measurements for two satellites in low Earth orbit separated by baselines of 100 km.

• 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.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.404-411
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• 2022

The main function in operating the satellite navigation system is to accurately determine the orbit of the navigation satellite and transmit it as a navigation message. In this study, we developed software to determine the orbit of a navigation satellite by combining an extended Kalman filter and an accurate dynamic model. Global positioning system (GPS) and quasi-zenith satellite system (QZSS) orbit determination was performed using international gnss system (IGS) ground station observations and user range error (URE), a key performance indicator of the navigation system, was calculated by comparison with IGS precise ephemeris. When estimating the clock error mounted on the navigation satellite, the radial orbital error and the clock error have a high inverse correlation, which cancel each other out, and the standard deviations of the URE of GPS and QZSS are small namely 1.99 m and 3.47 m, respectively. Instead of estimating the clock error of the navigation satellite, the orbit was determined by replacing the clock error of the navigation message with a modeled value, and the regional correlation with URE and the effect of the ground station arrangement were analyzed.