• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.682-687
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• 2013

Navigation is a crucial capability for all types of manned or unmanned vehicles. However, vehicle navigation in underwater environments still remains a challenging problem since GPS signals for position fixes are not available in the water. Terrain-referenced underwater navigation is an alternative navigation technique that utilizes geometric information of the subsea terrain to correct drift errors due to dead-reckoning or inertial navigation. Terrain-referenced navigation requires the description of an undulating terrain surface as a mathematical function or table, which often leads to a highly nonlinear estimation problem. Recently, PFs (Particle Filters), which do not require any restrictive assumptions about the system dynamics and uncertainty distributions, have been widely used for nonlinear filtering applications. However, PF has considerable computational requirements which used to limit its applicability to problems of relatively low state dimensions. This study proposes the use of a Rao-Blackwellized particle filter that is computationally more efficient than the standard PF for terrain-referenced underwater navigation involving a moderate number of states, and its performance is compared with that of the extended Kalman filter algorithm. The validity and feasibility of the proposed algorithm is demonstrated through numerical simulations.

• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.702-708
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• 2013

Underwater TRN (Underwater Terrain Referenced Navigation) estimates an underwater vehicle state by measuring a distance between the vehicle and undersea terrain, and comparing it with the known terrain database. TRN belongs to absolute navigation methods, which are used to compensate a drift error of dead reckoning measurements such as IMU (Inertial Measurement Unit) or DVL (Doppler Velocity Log). However, underwater TRN is different to other absolute methods such as USBL (Ultra-Short Baseline) and LBL (Long Baseline), because TRN is independent of the external environment. As a magnetic-field-based navigation, TRN is a kind of geophysical navigation. This paper develops an EKF (Extended Kalman Filter) formulation for underwater TRN. A filter propagation part is composed by an inertial navigation system, and a filter update is executed with echo-sounder measurement. For large-initial-error cases, an adaptive EKF approach is also presented, to keep the filter be stable. At the end, simulation studies are given to verify the performance of the proposed TRN filter. With simplified sensor and terrain database models, the simulation results show that the underwater TRN could support conventional underwater navigation methods.

• International Journal of Aeronautical and Space Sciences
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• 제14권1호
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• pp.85-90
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• 2013

This paper presents a study on terrain referenced navigation (TRN). The extended Kalman filter (EKF) is adopted as a filter method. A Jacobian matrix of measurement equations in the EKF consists of terrain slope terms, and accurate slope estimation is essential to keep filter stability. Two slope estimation methods are proposed in this study. Both methods are based on the least-squares approach. One is planar regression searching the best plane, in the least-squares sense, representing the terrain map over the region, determined by position error covariance. It is shown that the method could provide a more accurate solution than the previously developed linear regression approach, which uses lines rather than a plane in the least-squares measure. The other proposed method is weighted planar regression. Additional weights formed by Gaussian pdf are multiplied in the planar regression, to reflect the actual pdf of the position estimate of EKF. Monte Carlo simulations are conducted, to compare the performance between the previous and two proposed methods, by analyzing the filter properties of divergence probability and convergence speed. It is expected that one of the slope estimation methods could be implemented, after determining which of the filter properties is more significant at each mission.

• 한국군사과학기술학회지
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• 제20권3호
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• pp.307-314
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• 2017

Terrain referenced navigation(TRN) system is an attractive method for obtaining position based on terrain measurements and a terrain map. We focus on TRN systems based on the point mass filter(PMF) which is one of the recursive Bayesian method. In this paper, we propose two kinds of performance index for Bayesian filter. The proposed indices are based on entropy and mutual information from information theory. The first index measures roughness of terrain based on entropy of likelihood. The second index named by information gain, which is the mutual information between priori and posteriori distribution, is a quantity of information gained by updating measurement at each step. The proposed two indices are used to determine whether the solution from TRN is adequate for TRN/INS integration or not, and this scheme gives the performance improvement. Simulation result shows that the proposed indices are meaningful and the proposed algorithm performs better than normal TRN algorithm.

• Spatial Information Research
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• 제15권4호
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• pp.363-370
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• 2007

본 연구는 지형참조항법(TRN; Terrain Referenced Navigation)에 근거하는 헬리콥터 항법 시스템을 위한 기본 알고리즘을 개발하기 위해 수행되었다. 현재 본 연구에 위성 항법장치(GPS; Global Positioning System)로부터의 정보(X, Y, Z 좌표)는 비행체가 항로를 비행하는 중 매 92.8m의 수평거리로 환산하여 수신되는 것으로 가정하였다. 비행체는 3차원 직교 좌표 체계(Cartesian coordinate system)로 표현되는 수치지형모델(DTM; Digital Terrain Model)상에서 시점(Origination)-종점(Destination) 분석 기법에 의해 항로를 결정한다. 본 시스템은 우선 조종사에게 지형의 사전 인식을 위해 시점-종점 주변 3차원 지형도와 항로의 종단면도를 보여준다. 본 시스템은 직접적인 지상 충돌을 피하기 위해 지형 여유 층면(terrain clearance floor)의 개념을 도입, 기복 지형 표면에 일정 높이의 완충 공간을 설정한다. 만약 비행체가 항행 중 완충 공간에 접근하게 되면 본 시스템은 실시간으로 즉시 경고음과 메시지를 발한다(Matlab 메뉴를 사용하였음). 물론 헬리콥터의 이착륙 시에는 불필요한 경고를 발생시키지 않기 위해 완충 공간 조정은 가능하다. 수치지형모델은 (주)첨성대가 확보하고 있는 3초 간격의 DTM을 채택, 작성하였다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2010년 춘계학술발표회 논문집
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• pp.161-164
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• 2010

The study on terrain referenced navigation has been proceeded from 1940s in advanced country with the object of military. In this study, the analysis regarding algorithm developed using cross-correlation matching algorithm and extended Kalman filter and simulation will be introduced. As a result, the standard deviation of position error from cross-correlation matching algorithm has been calculated 34.3m. It meant that the result has stable accuracy on the navigation. However, further study on terrain referenced navigation based on analysis of various topographic characteristics should be performed.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.131-139
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• 2013

In recent years alternative navigation system such as a DBRN (Data-Base Referenced Navigation) system using geophysical information is getting attention in the military navigation systems in advanced countries. Specifically TRN (Terrain Referenced Navigation) algorithm research is important because TRN system is a practical DBRN application in South Korea at present time. This paper presents an integrated navigation algorithm that combines a linear profile-based TRN and INS (Inertial Navigation System). We propose a correlation analysis method between TRN performance and terrain roughness index. Then we propose a conditional position update scheme that utilizes the position output of the conventional linear profile type TRN depending on the terrain roughness index. Performance of the proposed algorithm is verified through Monte Carlo computer simulations using the actual terrain database. The results show that the TRN/INS integrated algorithm, even when the initial INS error is present, overcomes the shortcomings of linear profile-based TRN and improves navigation performance.

• 한국측량학회지
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• 제28권1호
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• pp.73-82
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• 2010

지형 참조 항법 기술 중 하나인 TERCOM은 순항미사일에 장착되어 있는 시스템으로 현재까지도 지속적으로 연구되고 있는 기술이다. 본 논문에서는 영역기반 정합 기법과 확장형 칼만필터를 이용하여 TERCOM에 기반한 지형 참조 항법을 시뮬레이션을 통해 분석하였다. 영역기반 정합의 유사성 분석에는 평균제곱오차 알고리즘과 상호상관정합 알고리즘을 적용하였다. 기압 고도계와 레이더 고도계, SRTM DTM을 탑재한 항체가 시속 1000km로 545초 간 장방형 궤적으로 비행하도록 시뮬레이션 하였으며, 그 결과 평균제품오차 기반 알고리즘의 거리 오차의 표준연차는 99.6m 상호상판정합 기반 알고리즘은 34.3m로 상호상관정합 기반 알고리즘이 상대적으로 지형에 덜 민감하고 두 알고리즘 모두 지형의 기복 정도에 따라 항법 정밀도의 편차가 큰 것으로 나타났다. 따라서 완만한 지형에도 민감한 알고리즘과 관성항법 적분오차 증가에 따라 적절한 탐색영역의 크기 결정, 비행환경에 따라 요구되는 최적의 지형 데이터베이스의 해상도 결정 등에 대한 연구가 수행되어야 할 것으로 판단된다.

• 한국측량학회지
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• 제34권4호
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• pp.373-382
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• 2016

In this study, an EKF (Extended Kalman Filter) based database reference navigation using both gravity gradient and terrain data was performed to complement the weakness of using only one type of geophysical DB (Database). Furthermore, a new algorithm which combines the EKF and profile matching was developed to improve the stability and accuracy of the positioning. On the basis of simulations, it was found that the overall navigation performance was improved by the combination of geophysical DBs except the two trajectories in which the divergence of TRN (Terrain Referenced Navigation) occurred. To solve the divergence problem, the profile matching algorithm using the terrain data is combined with the EKF. The results show that all trajectories generate the stable performance with positioning error ranges between 14m to 23m although not all trajectories positioning accuracy is improved. The average positioning error from the combined algorithm for all nine trajectories is about 18 m. For further study, a development of a switching geophysical DB or algorithm between the EKF and the profile matching to improve the navigation performance is suggested.

• 한국항공우주학회지
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• 제40권11호
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• pp.979-987
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• 2012

본 논문에서는 무인전투기의 지형추종을 위한 궤적생성, 유도, 항법 알고리즘을 구현하고 이를 통합하였다. 적 방공망 제압과 같은 위험한 임무를 수행하는 무인전투기는 적의 대공방어망으로부터 생존성을 높이기 위해서 지면을 근접하여 비행하는 지형추종 알고리즘이 필수적으로 요구된다. 무인전투기가 지형추종 비행을 하기 위해서는 경로생성, 유도, 그리고 항법 분야 알고리즘이 통합되어야 한다. 본 논문에서는 항법 알고리즘으로 GPS가 교란된 상황을 대비하여 비선형 필터 기반의 지형참조 항법을 사용하였다. 경로생성을 위해 지형추종에 적합한 경로생성 기법으로 보로노이 다이어그램을 이용하여 적의 대공망을 회피하는 수평경로를 생성하고, Cubic Spline 기법을 사용하여 정해진 수평경로 상에서 지면과의 근접비행이 가능한 수직경로를 생성하였다. 유도 알고리즘으로 전방주시점 기반의 유도법칙인 Follow-the-Carrot 기법과 Pure Pursuit 기법을 사용하여 생성된 경로를 추종하게 하였다. 제안한 통합알고리즘의 성능을 검증하기 위하여 수치 시뮬레이션을 수행하였다.