• Spatial Information Research
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• v.16 no.3
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• pp.373-383
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• 2008

LiDAR, unlike satellite imagery and aerial photographs, which provides irregularly distributed three-dimensional coordinates of ground surface, enables three-dimensional modeling. In this study, urban area was classified based on 3D information collected by LiDAR. Morphological and spatial properties are determined by the ratio of ground and non-ground point that are estimated with the number of ground reflected point data of LiDAR raw data. With this information, the residential and forest area could be classified in terms of height and density of trees. The intensity of the signal is distinguished by a statistical method, Jenk's Natural Break. Vegetative area (high or low density) and non-vegetative area (high or low density) are classified with reflective ratio of ground surface.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.101-115
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• 2018

The Long Valley area and its surroundings are part of a major volcano system where inflation occurred in the resurgent dome in the 1990s. We used ENVISAT data to monitor surface deformation of the Long Valley area and its surroundings after the inflation, from 2003-2010. To retrieve the time series of the deformation, we applied the refined Small BAseline Subset (SBAS) algorithm which is improved using an iterative approach to minimize unwrapping error. Moreover, ascending and descending data were used to decompose the horizontal and vertical deformation in detail. To confirm refined SBAS results, we used GPS dataset. The InSAR errors are estimated as ${\pm}1.0mm/yr$ and ${\pm}0.8mm/yr$ from ascending and descending tracks, respectively. Compare to the previous study of 1990s over the Long Valley and its surroundings, Paoha Island and CASA geothermal area still subside. The deformation pattern in the Long Valley area during the study period (2003-2010) went through both subsidence (2003-2007) and slow uplift(2007-2010) episodes. Our research also shows no deformation signal near McGee Creek. Our study provided a better understanding of the surface changes of the indicators in the 1990s and 2000s.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.851-853
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• 2013

Recently, location-based service as the developed continuously, interest in positioning technology is increasing. As the most famous indoor positioning technology, WPS is a positioning technology using WiFi, which can complement the limits of the indoor positioning to have a GPS. In this paper, to provide a system for monitoring the position of the inside of the user based on the position information that using the RSSI signal of the wireless AP based WPS technology, they grip the location information of the mobile nodes in the indoor. If using the method proposed, it is expected to be applied to various services it is possible to apply the WPS, this is because it is possible to estimate in real time the location distribution of mobile nodes in the indoor.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.33-41
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• 2008

Telematics system includes the "vehicle remote diagnosis technology", "driving pattern analysis technology" which are commercially attractive in the real life. To implement those technologies, we need vehicle signal interface, vehicle diagnosis interface, accelerometer/yaw-rate sensor interface, GPS data processing, driving pattern analysis, and CDMA data processing technique. Based on these technologies, we analyze the error existence by diagnosing the EMS(Engine Management System), TMS(Transmission Management System), ABS/TCS, A/BAG in real time. And we are checking about a driving pattern and management of the vehicle, which are sent to the information center through the wireless communication. These database results will make the efficient vehicle and driver management possible. We show the effectiveness of our results by field driving test after completing the H/W & S/W design and implementation for vehicle remote diagnosis and driving pattern analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8A
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• pp.633-643
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• 2003

UWB impulse radio signals have an very short duration, extremely wide bandwidth and share the same frequency spectrum with other existing systems. It was determined by the Federal Communications Commission (FCC) that UWB systems could cause interference with other systems, such as Global Positioning System (GPS) for example. Therefore, at present. the FCC has restricted the use of UWB systems to frequencies above 3.1㎓. In this paper, We evaluated performance of UWB system using proposed pulses in ［1］［2］ that are strictly limited in time to remove interference while, at the same time, contain their power distribution to a frequency band from 3.1㎓ to 10.6㎓. In particular, We evaluated the BER Performance in relation to system parameters such as pulse duration. $\delta$, the number of users. Nu. and the number of symbols, M. We found the optimal pulse duration $\delta$ through computer simulation using developed UWB pulses in ［1］［2］. It is shown that performance evaluation between the UWB communication system using these UWB pulses ［1］［2］and the Gaussian monocycle pulse in M-ary PPM and BPSK schemes. These results can be contributed to construct M-ary PPM UWB communication system in terms of multiuser parameters and pulse duration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.390-396
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• 2015

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalizations of LBS is the accurate estimating position for mobile object. Focusing on an image sensor deployed in smart phone, we develop a LED based positioning estimation framework. The developed approaches can strengthen the advantages of independent indoor applicability of LED. The estimation of LED based positioning is effectively applied to any indoor environment. We put a focus especially on the algorithmic framework. of image processing of smart phone. From LED lighting, we can obtain a typical signal image which contains the unique positioning information. Furthermore test-bed based on smart phone platform is practically developed and all data have been harvested from the actual measurement of test indoor area. This can approve the practical usefulness of proposed framework.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.370-388
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• 2015

The localization of multi-agents, such as people, animals, or robots, is a requirement to accomplish several tasks. Especially in the case of multi-robotic applications, localization is the process for determining the positions of robots and targets in an unknown environment. Many sensors like GPS, lasers, and cameras are utilized in the localization process. However, these sensors produce a large amount of computational resources to process complex algorithms, because the process requires environmental mapping. Currently, combination multi-robots or swarm robots and sensor networks, as mobile sensor nodes have been widely available in indoor and outdoor environments. They allow for a type of efficient global localization that demands a relatively low amount of computational resources and for the independence of specific environmental features. However, the inherent instability in the wireless signal does not allow for it to be directly used for very accurate position estimations and making difficulty associated with conducting the localization processes of swarm robotics system. Furthermore, these swarm systems are usually highly decentralized, which makes it hard to synthesize and access global maps, it can be decrease its flexibility. In this paper, a simple pyramid RAM-based Neural Network architecture is proposed to improve the localization process of mobile sensor nodes in indoor environments. Our approach uses the capabilities of learning and generalization to reduce the effect of incorrect information and increases the accuracy of the agent's position. The results show that by using simple pyramid RAM-base Neural Network approach, produces low computational resources, a fast response for processing every changing in environmental situation and mobile sensor nodes have the ability to finish several tasks especially in localization processes in real time.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.241-246
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• 2006

This paper describes two kinds of personal hand-held electronic devices to support marine leisure safety. The one is Radar response-type safety device triggering by the pulse signal from a commercial 9GHz-band Radar to provide quick search and rescue with combined civilian-government-military fleets. The other one is M-RFID (Marine Radio Frequency IDentification) based safety electronic device using 900MHz Tx/Rx with spread spectrum frequency hopping and GPS. Through the field tests at sea using Korea Coast Guard's warship the operating performances are verified. Further plan for practical use of each device was also discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.80-80
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• 2016

GPS로 대표되는 위성항법시스템(GNSS : Global Navigation Satellite System)은 지구 주위를 돌면서 연속적으로 항법신호를 보내고 있다. 그 중 지구표면으로부터 반사되는 항법신호를 수신하고 해석함으로써 지구표면에 관한 정보를 취득할 수가 있다. GPS로 대표되는 항법신호는 L밴드를 사용하기 때문에 토양수분의 변화 등에 대한 반사강도의 감도가 비교적 높다고 알려져 있으며, 토양수분 측정 등에 사용할 수 있다. 뿐만 아니라 경량화, 소형화하기 쉬운 점, 능동적 마이크로웨이브 리모트센싱시스템(Active Microwave Remote Sensing System)과 달리 스스로 신호를 발사하지 않기 때문에 관측의 스텔스성(Stealth)dl 뛰어난 점 등의 장점을 가지고 있다. 또한 향후 10년 이내에 준천정위성(QZSS), Galileo, COMPAS, IRNSS 등 많은 위성항법시스템이 본격 운용되어 GPS와 함께 120기 정도의 항법위성이 항법신호를 송신할 예정이므로 이용 가능성은 크게 늘어날 것으로 기대된다.한편, 항법위성을 이용한 바이스테이틱 리모트센싱은 반사파의 강도가 상당히 미약하기 때문에 정량적 계측모델의 구축은 미미한 상태이다. 즉, 지상 타워에서의 관측, 항공기에서의 관측, 소형 위성에서의 관측 등이 수행되고 있으나, 타워관측과 같이 지상의 거의 동일한 장소를 계속적으로 관측하는 경우를 제외한 기존의 연구에서는 토지의 피복상황이나 토양수분 등의 상관관계를 제시하는 수준으로써 정량적인 계측방법은 아직 확립되어 있지 않다. 이러한 관점에서 본 연구에서는 GPS위성으로부터의 항법신호를 이용하여 지구표면에 관한 정보를 얻는 바이스테이틱 리모트센싱(Bi-static Remote Sensing) 기술을 바탕으로 육지면과 해면의 판별에 신호특성이 어떻게 유효한가를 실험적으로 밝혔다. 이러한 기술은 토양수분 측정 등 수자 원인자를 추출하는데 유용할 뿐만 아니라 수면의 고도 측정, 해상풍 산출 등에도 응용 가능하다.

• Journal of Platform Technology
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• v.11 no.5
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• pp.97-103
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• 2023

Unlike GPS, which is an outdoor positioning technology that is universally and uniformly used all over the world, various technologies are still being developed in the field of indoor positioning technology. In order to acquire accurate indoor location information, a standard of representative indoor positioning technology is required. Recently, indoor positioning technology is expanding into the Real Time Location Service (RTLS) area based on high-precision location data. Accordingly, a new type of indoor positioning technology is being proposed. Thanks to the development of artificial intelligence, artificial intelligence-based indoor positioning technology using wireless signal data of a smartphone is rapidly developing. At this time, in the process of collecting data necessary for artificial intelligence learning, data that is distorted or inappropriate for learning may be included, resulting in lower indoor positioning accuracy. In this study, we propose a data preprocessing technology for artificial intelligence learning to obtain improved indoor positioning results through the refinement process of the collected data.