• 대한원격탐사학회지
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• 제26권6호
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• pp.629-644
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• 2010

A real-time image georeferencing system requires all inputs to be determined in real-time. The intrinsic camera parameters can be identified in advance from a camera calibration process while other control information can be derived instantaneously from real-time GPS/INS data. The bottleneck process is tie point acquisition since manual operations will be definitely obstacles for real-time system while the existing extraction methods are not fast enough. In this paper, we present a fast-and-automated image matching technique based on the KLT tracker to obtain a set of tie-points in real-time. The proposed work accelerates the KLT tracker by supplying the initial guessed tie-points computed using the GPS/INS data. Originally, the KLT only works effectively when the displacement between tie-points is small. To drive an automated solution, this paper suggests an appropriate number of depth levels for multi-resolution tracking under large displacement using the knowledge of uncertainties the GPS/INS data measurements. The experimental results show that our suggested depth levels is promising and the proposed work can obtain tie-points faster than the ordinary KLT by 13% with no less accuracy. This promising result suggests that our proposed algorithm can be effectively integrated into the real-time image georeferencing for further developing a real-time surveillance application.

• 제어로봇시스템학회논문지
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• 제8권12호
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• pp.1067-1075
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• 2002

The system error model for the compensation of the low-cost personal navigation system is derived and the error compensation method using GPS is also proposed. The walking navigation system (WNS) that calculates navigation information through walking detection has small error than INS, but the error also increases with time. In order to improve reliability of the system regardless of time, WNS is integrated with GPS. Since WNS is usually used in urban area, the blockage of CPS signal is frequently occurred. Therefore tightly coupled Kalman filter is used for the integration of WNS and GPS. In this paper, the system model for the design of tightly coupled Kかm filter is designed and measurement is linearized in consideration of moving distance error. It is shown by Monte Carlo simulation that the error is bounded even through the number of visible satellite is less than 4.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.118-121
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• 2007

In recent years, the hyperspectral instruments with high spatial and high spectral resolution have become an important component of wide variety of earth science applications. The primary mission of the proposed Compact Airborne Imaging Spectrometer System (CAISS) in this study is to acquire and provide full contiguous spectral information with high quality spectral and spatial resolution for advanced applications in the field of remote sensing. The CAISS will also be used as the vicarious calibration equipment for the cross-calibration of satellite image data. The CAISS consists of six physical units: the camera system, the Jig, the GPS/INS, the gyro-stabilized mount, the operating system, and the power inverter and distributor. Additionally, the calibration instruments such as the integrated sphere and spectral lamps are also prepared for the radiometric and spectral calibration of the CAISS. The CAISS will provide high quality calibrated image data that can support evaluation of satellite application products. This paper summarizes the design, development and major characteristic of the CAISS.

• ETRI Journal
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• 제30권1호
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• pp.59-67
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• 2008

The necessity for the precise time synchronization of measurement data from multiple sensors is widely recognized in the field of global positioning system/inertial navigation system (GPS/INS) integration. Having precise time synchronization is critical for achieving high data fusion performance. The limitations and advantages of various time synchronization scenarios and existing solutions are investigated in this paper. A criterion for evaluating synchronization accuracy requirements is derived on the basis of a comparison of the Kalman filter innovation series and the platform dynamics. An innovative time synchronization solution using a counter and two latching registers is proposed. The proposed solution has been implemented with off-the-shelf components and tested. The resolution and accuracy analysis shows that the proposed solution can achieve a time synchronization accuracy of 0.1 ms if INS can provide a hard-wired timing signal. A synchronization accuracy of 2 ms was achieved when the test system was used to synchronize a low-grade micro-electromechanical inertial measurement unit (IMU), which has only an RS-232 data output interface.

• 한국측량학회지
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• 제23권3호
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• pp.323-330
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• 2005

현재 Direct Georeferencing은 지난 10여년 적용되어오던 GPS-항측의 단점인 항공사진의 6개 외부표정요소중 단지 투영중심의 위치만 제공하던 약점을 극복하고 실무에 보편적으로 적용되고 있는 실정이다. 이의 가장 큰 장점은 지상기준점 측량작업의 절감내지는 이를 완전히 생략할 수 있다는 점이다. 본 본문은 상용의 GPS/IMU 를 이용하여 외부표정요소 결정에 대한 실힘 결과를 소개하였다. 실힘을 위하여 사진축척 1:5,000의 대축척과 1:20,000의 중축척으로 촬영한 관측자료를 처리하여 사진축척의 변화를 고려한 외부표정요소 결정의 정확도 및 결합블럭조정의 특성 등 다양하고 의미 있는 결과들을 도출하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1535-1536
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• 2008

GPS/INS/지자기 컴파스 통합 항법 시스템에서 지자기 컴파스의 이상 검출 방법을 제안하였다. 지자기 컴파스의 이상은 Hard iron과 Soft iron 효과에 의하여 발생하므로 이와 관련된 값을 통합 필터 측정치의 시험 통계치로 이용하여 검출하는 방법을 제안하였다. 제안한 방법의 효용성을 모의 실험과 차량 실험을 통하여 검증하였다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.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.

• 한국군사과학기술학회지
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• 제16권2호
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• pp.95-100
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• 2013

Localization is very important for the autonomous navigation of Unmanned Ground Vehicles; however, it is difficult that they have a precise Inertial Navigation System(INS) sensor, especially Small Unmanned Ground Vehicle(SUGV). Moreover, there are some condition such as denial of global position system(GPS), GPS/INS integrated system is not robust. This paper proposes the estimation algorithm with optical flow sensor and INS. Being compared with previous researches, the proposed algorithm is suitable for skid steering vehicles. We revised the measurement model of previous research for the accuracy of side direction position. Experimental results were performed to verify the algorithm, and the result showed an excellent performance.

• 대한토목학회논문집
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• 제29권1D호
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• pp.135-143
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• 2009

GPS 반송파를 사용하는 GPS/INS 통합 측위 기술은 서로가 가지는 기술적 한계를 상호 극복하여 그 성능을 최대화 할 수 있어 측량과 항법의 다양한 분야에 활용되고 있다. 그러나 GPS/INS 통합 측위을 통하여 수 센티미터의 정확도를 확보하기 위해서는 기준국과 이동국 수신기 사이의 간격이 10~20Km 이내로 제한되어야 하는 단점을 가지고 있으며 이는 두 시스템 관측데이터를 통합 처리하더라도 그 정확도는 여전히 GPS 위성궤도 오차, 전리층 영향 그리고 대류권 지연과 같은 기선장에 따른 오차의 영향을 받기 때문이다. 이것은 3대 이상의 기준국 관측데이터를 사용하여 기선장에 따른 오차 보정량을 추정하여 이동국 관측데이터에서 그 영향을 최소화하여 극복 할 수 있다. 따라서 본 논문에서는 다중의 기준국 관측데이터를 사용하여 기선장에 따른 오차 보정량 결정을 위한 기준국 반송파 미지정수 결정, 칼만필터에 의한 기선장에 따른 오차 추정 그리고 기준국과 이동국의 기하관계에 의한 오차 보간을 통한 보정량 산출 알고리즘 제안하고 실제 관측데이터 처리를 통해 그 성능을 평가 하였다.

• 한국측량학회지
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• 제23권4호
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• pp.359-366
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• 2005

3차원 지형정보에 대한 사용자 요구의 증가에 따라 GPS/INS, 레이저 스캐너 시스템이 조합된 항공레이저측량 기술이 각광받고 있다. 본 논문에서는 항공레이저측량(LiDAR) 시스템의 정확도 확보를 위해 검정장에서의 측량데이터를 바탕으로 시스템 검정을 실시하였다. 검정결과, 수평 정확도는 ${\pm}15{\sim}30\;cm$ 이내, 수직정확도는 ${\pm}15cm$ 이내로 나타났다. 이를 통해 항공레이저측량 데이터를 이용하여 정밀 DEM 및 등고선 제작. 도시지역의 3차원 모델 제작, 엔지니어링 설계 등의 활용에 충분함을 입증하였다.