• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.2
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• pp.272-279
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• 2016

Many researches on use of local ground navigation systems can be found to overcome vulnerability of GNSS. Effective use of an altimeter is proposed in GNSS/DME integrated navigation systems. A weighted DOP based on statistics of measurement error is derived for a given vehicle motion trajectory. From the derived DOP, the vertical error is estimated. By comparing the estimated vertical error with error specification of the altimeter, use of the altimeter is determined in the GPS/DME integrated navigation systems. In order to show effectiveness of the proposed method, 50 times Monte-Carlo simulations were performed for a GPS/DME integrated navigation system. The results show that the proposed method gives more accurate navigation outputs when the number of GPS satellites in view varies.

• Journal of Astronomy and Space Sciences
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• v.20 no.4
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• pp.365-374
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• 2003

Satellite formation flying is currently an active area of research in the aerospace engineering. So it has been researched by various authors. In this study, a tracking controller using sliding mode techniques was designed to control a satellite for the satellite formation flying. In general, Hill's equations are used to describe the relative motion of the follower satellite with respect to the leader satellite. However the modified Hill's equations considering the $J_2$ perturbation were used for the design of sliding mode controller. The extended Kalman filter was applied to estimate the state vector based on the measurements of relative distance and velocity between two satellites. The simulation results show that the follower satellite tracks the desired trajectory well by thruster operations based on the sliding mode control law.

• Journal of Navigation and Port Research
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• v.33 no.9
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• pp.603-608
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• 2009

In this paper, a 3m-class free running model ship will be introduced with its manoeuvring performance experiments. The results of turning circle test and zig-zag test will be explained. The developed system are equipped with GPS, main control computer, wireless LAN, IMU (Inertial Measurement Unit), self-propulsion propeller and driving rudder. Its motion can be controlled by RC (Radio Control) and wireless LAN from land based center. Automatic navigation is also available by pre-programmed algorithm. The trajectory of navigation can be acquired by GPS and it provides us with important data for ship's motion control experiments. The results of manoeuvring performance experiment have shown that the developed free running model ship can be used to verify the test of turning circle and zig-zag. For next step, other experimental researches such as ship collision avoidance system and automatic berthing can be considered in the future.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1254-1257
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• 2015

최근 위치기반서비스에 관심이 집중되면서 GPS 궤적에 관심 지점(POI: Point of Interest) 정보를 결합한 시맨틱 궤적(Semantic Trajectory)이 주목 받고 있다. 기존 연구에서는 GPS 궤적으로부터 속력을 계산하여 사용자가 정지했을 만한 예측 정지 구간(PSI: Predictive Stop Interval)과 실제로 방문했을 것이라 예상되는 POI를 선정하여 시맨틱 궤적을 생성하였다. 그러나 CPU에서는 대용량의 GPS 궤적에 대해서 PSI를 구할 시 많은 연산 때문에 시간이 오래 걸리는 문제가 있다. 이에 본 논문에서는 GPU의 병렬성을 이용하여 PSI를 생성하는 알고리즘을 제안한다. 제안하는 GPU를 이용한 PSI 생성 알고리즘은 기존의 CPU를 사용한 PSI 알고리즘보다 최대 5배 이상 속도 향상이 있으며, PSI의 개수가 많을수록 성능상의 이득이 더 큰 장점을 가지고 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.587-590
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• 2020

스마트폰, GPS 장비, 위치 기반 소셜네트워크의 발달로 방대한 이동 경로 데이터 수집이 가능하게 됐다. 이를 통해 다양한 분야에서 GPS 데이터를 가지고 사람의 이동성을 분석하고 POI를 예측하는 기회가 많아졌다. 실생활에서 사람의 이동성은 다양한 상황에 영향을 받지만, 실제 GPS 데이터는 위치, 시간 정보의 수준이다. 따라서 다양한 상황을 내재하는 정보가 사람의 이동성 분석과 POI 예측에 필요하다. 본 논문에서는 POI의 순위, 사용자의 POI 활동, 카테고리 선호도 같은 맥락적 특징을 이용하여 이에 관련된 상황에 맞는 POI 시퀀스를 예측하는 Contextual LSTM 기반 딥러닝 기법을 제안한다. Contextual LSTM은 사람의 이동성에 영향을 주는 시퀀스의 맥락적 특징을 모델에 통합하기 위해 LSTM을 확장한다. 제안된 기법은 HITS 알고리즘과 여러 제약조건 기반으로 추출한 맥락적 특징별로 딥 러닝 모델에 통합하여 각각 POI 시퀀스를 검출했으며, 다양한 맥락적 특징에 대해서 공공 데이터와 수집한 데이터로 평가하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.95-104
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• 2015

Recently, collecting and analyzing method of users location has been studied due to the development of mobile devices. There is analyzing method using Semantic Location History in order to identify of characteristics and extract pattern and predict trajectory of users. We should extraction of Stay Point in order to use Semantic Location History. The Conventional extraction method of Stay Point is not accuracy of location of Stay Points because it does not specify the GPS log of users. Also, Conventional extraction method of Stay Point cannot distinguish indoors and outdoors. In this paper, we implement extraction method of Stay Point in which specify the GPS log of users and extraction of Stay Point at indoors only. Stay Point(nearSP) specifies the nearest GPS log of users from generated Stay Point by conventional extraction method. And, Stay Point(indoorSP) specifies the GPS log of users that user get into the building. Our experimental results, accuracy of Stay Point is improved, and capacity of output data decrease than Conventional extraction method. Also, we were able to distinguish Stay Point of indoors and outdoors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1236-1251
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• 2013

Sharing geo-tagged photos has been a hot social activity in the daily life because these photos not only contain geo information but also indicate people's hobbies, intention and mobility patterns. However, the present raw geo-tagged photo routes cannot provide information as enough as complete GPS trajectories due to the defects hidden in them. This paper mainly aims at analyzing the large amounts of geo-tagged photos and proposing a novel travel route restoring method. In our approach we first propose an Interest Measure Ratio to rank the hot spots based on density-based spatial clustering arithmetic. Then we apply the Hidden Semi-Markov model and Mean Value method to demonstrate migration discipline in the hot spots and restore the significant region sequence into complete GPS trajectory. At the end of the paper, a novel experiment method is designed to demonstrate that the approach is feasible in restoring route, and there is a good performance.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.9-21
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• 2007

In this paper, the hybrid methods are suggested, which use the direction angle information to present running trajectory and track the past locations through a small amount of vehicle's location information. In order to prove the effectiveness of the new technique suggested here, vehicle's location information are collected by running the vehicles moving objects under various conditions. Using the location informations and direction angle information collected with time intervals, the vehicl e's location information is abstracted, compared and analyzed. and I have proved that the suggested techniques are more effective by comparing them with others in various methods such as GPS TrackMaker, difference image techniques, consistency comparison, quantity comparison, vehicle's running distances and so on.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.85-90
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• 2017

Various mobile devices are spreading in recent developments in mobile computing environments. Especially the popularity of mobile devices equipped with GPS has become widespread, and various application services utilizing location information are born. In this paper, we propose a system model for storing and managing the trajectory of moving objects, which is the set of location information of moving objects acquired in continuous time, and the UDF (User-Defined Functions) based trajectory index method which can quickly query the large data set of moving object and the Pre-Materialized table method. Then we compare and evaluate the performance of each method through experiments. Experimental results show that the Pre-Materialized table method is about 1.2 times faster than the UDF based trajectory index method on execution time.

• Journal of Construction Engineering and Project Management
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• v.8 no.1
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• pp.10-21
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• 2018

Many construction projects involve a plethora of safety-related problems that can cause loss of productivity, diminished revenue, time overruns, and legal challenges. Incorporating data collection and analytics methods can help overcome the root causes of many such problems. However, in a dynamic construction workplace collecting data from a large number of resources is not a trivial task and can be costly, while many contractors lack the motivation to incorporate technology in their activities. In this research, an Android-based mobile application, Preemptive Construction Site Safety (PCS2) is developed and tested for real-time location tracking, trajectory prediction, and prevention of potential collisions between workers and site hazards. PCS2 uses ubiquitous mobile technology (smartphones) for positional data collection, and a robust trajectory prediction technique that couples hidden Markov model (HMM) with risk-taking behavior modeling. The effectiveness of PCS2 is evaluated in field experiments where impending collisions are predicted and safety alerts are generated with enough lead time for the user. With further improvement in interface design and underlying mathematical models, PCS2 will have practical benefits in large scale multi-agent construction worksites by significantly reducing the likelihood of proximity-related accidents between workers and equipment.