• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.99-99
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• 2004

• Spatial Information Research
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• v.21 no.6
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• pp.57-67
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• 2013

GPS based car navigation systems show significant problems in such environment as a tunnel, a road surrounded by high buildings. In this study, we thus propose a method to determine positions and attitudes using only in-vehicle sensory data without a GPS. To check the feasibility of this method, we constructed a system to acquire in-vehicle sensory data and reference data simultaneously. We acquired test data using this system, estimated the trajectory based on the proposed method and evaluated the accuracy of both the sensory data and the trajectory. The speed and angular velocities provided by the in-vehicle sensors include 1.1 km/h and 0.8 deg/s RMS errors, respectively. The estimated trajectory using these data shows 20.8 m RMS errors for a 15 minute drive. In future, if we further combine additional sensors such as a camera and a GPS, we can achieve a high accurate navigation system at a low cost without an expensive high-grade external IMU.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.897-898
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• 2009

본 논문은 사용자의 일상적인 이동 경로 패턴을 분석하여 일상화 지수를 측정하고, 이를 통해 GPS 신호 검색 주기를 동적으로 변경하는 동적 GPS 신호 검색 주기 변경 시스템을 제안한다. 고정된 GPS 신호 검색 주기는 불필요하게 많은 전력을 소모하기 때문에 제안 시스템을 이용하여 이동 단말기의 전력 소모 문제를 개선할 수 있다.

• Journal of Positioning, Navigation, and Timing
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• v.1 no.1
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• pp.45-49
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• 2012

The flight performance evaluation of navigation system is very significant because the reliability of navigation data directly affect the safety of aircraft. Especially, the high-level navigation system such as DGPS/INS, need more precise flight performance evaluation method. The performance analysis is evaluated by comparing between the navigation system in aircraft and reference trajectory which is more precise than navigation system in aircraft. In order to verify DGPS/INS performance of m-level, the GPS receiver, which is capable post-processed Carrier-phase Differential GPS(CDGPS) method of cm-level, have to be used as reference system. The DGPS/INS is estimated the Center of Gravity (CG) point of aircraft to offer precise performance while the reference system is output the position of GPS antenna which is mounted on the outside of aircraft. Therefore, in order to more precise performance evaluation, it needs to compensate the lever arm and coordinates transformation. This paper use quaternion and Direct Cosine Matrix(DCM) methods as coordinate transformation matrix in lever arm compensation of CDGPS reference trajectory. And it compares NED errors of DCM and quaternion transformation in lever arm of reference trajectory via DGPS/INS result.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.133-142
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• 2021

Travel pattern recognition is widely used in many aspects such as user trajectory query, user behavior prediction, interest recommendation based on user location, user privacy protection and municipal transportation planning. Because the current recognition accuracy cannot meet the application requirements, the study of travel pattern recognition is the focus of trajectory data research. With the popularization of GPS navigation technology and intelligent mobile devices, a large amount of user mobile data information can be obtained from it, and many meaningful researches can be carried out based on this information. In the current travel pattern research method, the feature extraction of trajectory is limited to the basic attributes of trajectory (speed, angle, acceleration, etc.). In this paper, permutation entropy was used as an eigenvalue of trajectory to participate in the research of trajectory classification, and also used as an attribute to measure the complexity of time series. Velocity permutation entropy and angle permutation entropy were used as characteristics of trajectory to participate in the classification of travel patterns, and the accuracy of attribute classification based on permutation entropy used in this paper reached 81.47%.

• Journal of Astronomy and Space Sciences
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• v.20 no.4
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• pp.359-364
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• 2003

In this paper, we present multi-sensor data fusion for telematics application. Successful telematics can be realized through the integration of navigation and spatial information. The well-determined acquisition of vehicle's position plays a vital role in application service. The development of GPS is used to provide the navigation data, but the performance is limited in areas where poor satellite visibility environment exists. Hence, multi-sensor fusion including IMU (Inertial Measurement Unit), GPS(Global Positioning System), and DMI (Distance Measurement Indicator) is required to provide the vehicle's position to service provider and driver behind the wheel. The multi-sensor fusion is implemented via algorithm based on Kalman filtering technique. Navigation accuracy can be enhanced using this filtering approach. For the verification of fusion approach, land vehicle test was performed and the results were discussed. Results showed that the horizontal position errors were suppressed around 1 meter level accuracy under simulated non-GPS availability environment. Under normal GPS environment, the horizontal position errors were under 40㎝ in curve trajectory and 27㎝ in linear trajectory, which are definitely depending on vehicular dynamics.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.250-256
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• 2012

Unmanned ground vehicles may be operated by remote control unit through the wireless communication or autonomously. However, the autonomous technology is still challenging and not perfectly developed. For some reason or other, the wireless communication is not always available. If wireless communication is abruptly disconnected, the UGV will be nothing but a lump of junk. What was worse, the UGV can be captured by enemy. This paper suggests a method, autonomous return technology with which the UGV can autonomously go back to a safer position along the reverse path. The suggested autonomous return technology for UGV is based on multi-correlated information based DB creation and matching. While SUGV moves by remote-control, the multi-correlated information based DB is created with the multi-sensor information; the absolute position of the trajectory is stored in DB if GPS is available and the hybrid MAP based on the fusion of VISION and LADAR is stored with the corresponding relative position if GPS is unavailable. In multi-correlated information based autonomous return, SUGV returns autonomously based on DB; SUGV returns along the trajectory based on GPS-based absolute position if GPS is available. Otherwise, the current position of SUGV is first estimated by the relative position using multi-sensor fusion followed by the matching between the query and DB. Then, the return path is created in MAP and SUGV returns automatically based on the MAP. Experimental results on the pre-built trajectory show the possibility of the successful autonomous return.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.183-189
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• 2009

Recently, PCS, PDA and mobile devices, such as the proliferation of spread, GPS (Global Positioning System) the use of, the rapid development of wireless network and a regular user even images, audio, video, multimedia data, such as increased use is for. In particular, video data among multimedia data, unlike the moving object, text or image data that contains information about the movements and changes in the space of time, depending on the kinds of changes that have sigongganjeok attributes. Spatial location of objects on the flow of time, changing according to the moving object (Moving Object) of the continuous movement trajectory of the meeting is called, from the user from the database that contains a given query trajectory and data trajectory similar to the finding of similar trajectory Search (Similar Sub-trajectory Retrieval) is called. To search for the trajectory, and these variations, and given the similar trajectory of the user query (Tolerance) in the search for a similar trajectory to approximate data matching (Approximate Matching) should be available. In addition, a large multimedia data from the database that you only want to be able to find a faster time-effective ways to search different from the existing research is required. To this end, in this paper effectively divided into a grid to search for the trajectory to the trajectory of moving objects, similar to the effective support of the search trajectory offers a new grid-based search techniques.

• KIISE Transactions on Computing Practices
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• v.22 no.4
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• pp.189-194
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• 2016

A trajectory is the motion path of a moving object. The advances in IT have made it possible to collect an immeasurable amount of various type of trajectory data from a moving object using location detection devices like GPS. The trajectories of moving objects are widely used in many different fields of research, including the geographic information system (GIS) field. In the GIS field, several attempts have been made to automatically generate digital maps of roads by using the vehicle trajectory data. To achieve this goal, the method to cluster the trajectories on the same road is needed. Usually, the $Fr{\acute{e}}chet$ distance measure is used to calculate the distance between a pair of trajectories. However, the $Fr{\acute{e}}chet$ distance measure requires prolonged calculation time for a large amount of trajectories. In this paper, we presented a fast heuristic algorithm to distinguish whether the trajectories are in close distance or not using the discrete $Fr{\acute{e}}chet$ distance measure. This algorithm trades the accuracy of the resulting distance with decreased calculation time. By experiments, we showed that the algorithm could distinguish between the trajectory within 10 meters and the distant trajectory with 95% accuracy and, at worst, 65% of calculation reduction, as compared with the discrete $Fr{\acute{e}}chet$ distance.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.2
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• pp.1-10
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• 2016

A GPS/SDINS/ST(Star Tracker) integrated sensor algorithm is more robust than the GPS/SDINS and the ST/SDINS systems on exploration of other planets. Most of the advanced studies shown that GPS/SDINS/ST integrated sensor with centralized Kalman filter was more accurate than those 2 integrated systems. The system, however, consist of a single filter, it is vulnerable to defects on failed data. To improve the problem, we work out a study using federated Kalman filter(No-Reset mode) and centralized Kalman filter with adaptive measurement fusion which known as robustness on fault. The simulation results show that the debasing influences are reduced and the computation is enable at least 100Hz. Further researches that the initial calibration in accordance with observability and applying the exploration trajectory are needed.