• 제어로봇시스템학회논문지
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• 제2권3호
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• pp.188-193
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• 1996

In this paper, an integrated navigation system based on GPS(Global Positioning System) and Dead-Reckoning (DR) is designed. For the calibration of DR, a self-calibration method and a GPS-based calibration method are proposed. From the field-test results, it is shown that DR can be successfully calibrated by the two proposed calibration methods. Also, a cascaded filter approach and a mixed-measurement algorithm are employed for GPS/DR integration. By using the newly proposed mixed-measurement algorithm, it is shown in simulation that the position error becomes smaller than by using only DR even if the number of visible GPS satellites is less than 4.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1450-1455
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• 2005

This paper describes a DR construction for land navigation and the sigma point based receding horizon Kalman FIR (SPRHKF) filter for DR/GPS hybrid navigation system. A simple DR construction is adopted to improve the performance both of the pure land DR navigation and the DR/GSP hybrid navigation system. In order to overcome the flaws of the EKF, the SPKF is merged with the receding horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, and etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can be occurred in the MEMS inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS hybrid navigation system for land navigation seamlessly.

• 로봇학회논문지
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• 제5권1호
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• pp.55-63
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• 2010

This paper describes performance improvement of GPS/DR Integration system using area decision algorithm and vehicle movement information. In GPS signal blockage area, i.e., tunnel and underground parking area, DR sensor errors are accumulated and navigation solution is gradually diverged. We use the car movement information according to moving area to correct the DR sensor error. Also, vehicle movement is decided as stop, straight line, turn and movement changing region through DR sensor data analysis. The car experiment is performed to verify the supposed method. The results show that supposed method provides small position and heading error than previous method.

• 제어로봇시스템학회논문지
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• 제12권2호
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• pp.174-185
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• 2006

This paper describes a DR construction for land navigation and the sigma point based receding horizon Kalman FIR (SPRHKF) filter for DR/GPS hybrid navigation system. A simple DR construction is adopted to improve the performance both of the pure DR navigation and the DR/GSP hybrid navigation system. In order to overcome the flaws of the EKF, the SPKF is merged with the receding horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, and etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can be occurred in the MEMS inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS hybrid navigation system for land navigation seamlessly.

• 제어로봇시스템학회논문지
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• 제7권3호
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• pp.269-275
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• 2001

In land navigation applications, two kinds of GPS/DR integration schemes are commonly used; the loosely-coupled integration scheme and the tightly-coupled one. The loosely-coupled integration filter has a simple structure and is easy to implement. When the number of visible satellites is insufficient, however, it cannot calibrate the errors of the DR sensors. On the contrary the tigthly-coupled integration filter can sup-press the growth of the error in the DR output even when the visibility is poor. However, it has larger com-putation load due to the state dimension and is inconsistent because of the variation in the measurement dimension. This paper presents a GPS/DR integration scheme with dual integration mode. During when the number of visible satellites is sufficient, the proposed scheme operates in a loosely-coupled integration mode. When the visibility becomes poor, it is switched into a tightly-coupled integration mode. Consequently, the pro-posed scheme can calibrate the DR sensors even when the visibility is poor. In addition, its computation time remains constant even if the number of visible satellites increases. Field experiment results show that the performance of the proposed integration method is almost similar to that of the tightly-coupled one.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.33.4-33
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• 2002

Recently, number of navigation system using GPS and other complementary sensor has been developed to offer high-position accuracy. In this paper, we developed navigation system for mobile robot integrating GPS and DR sensor information provided by fiber optic gyroscopes and encoder information. In the case of short-term applications, integrating this encoder and gyroscope through Kalman filter reliable positioning can be obtained. And for the long-term applications we developed GPS/DR Integration algorithm using Kalman filter

• 한국항행학회논문지
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• 제14권6호
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• pp.791-799
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• 2010

본 논문에서는 높은 정확도를 요구하는 육상교통분야에 활용할 수 있는 통합항법 알고리즘을 설계하고 차선이탈경보를 위한 모니터링 프로그램을 개발하였다. 차선이탈경보를 위해서는 차선 구분이 가능한 정확도 높은 위치정보가 필요하므로 GPS와 DR기반의 위치정보를 융합한 위치결정 알고리즘을 설계하였다. 설계한 통합항법 알고리즘의 검증을 위해서 실제 차량을 이용하여 데이터를 수집하고, 후처리한 결과를 모니터링 프로그램으로 확인하였다. 모니터링 프로그램은 주행동영상과 항공사진을 통해서 차로유지 및 차선이탈 유무를 확인할 수 있도록 제작하였다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.802-810
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• 2006

정밀한 열차제어를 위해서는 열차위치의 정확한 검지가 반드시 필요하다. 현재 일반적으로 널리 사용되고 있는 열차검지방법은 궤도회로를 이용하는 방법이다. 궤도회로는 구성이 단순하며, 신뢰성이 확보되는 장점이 있다. 하지만 열차는 궤도회로 위에서만 검지가 가능하므로 모든 지상구간에 궤도회로를 설치해야하며 설치 및 유지보수에 많은 비용이 소모된다. 또한 궤도회로는 폐전로 구성의 특성 때문에 불연속적인 위치검지만이 가능하다. 최근 통신기술의 발달과 차상제어장치의 첨단화에 따라 열차의 위치검지는 열차에서 직접 검지하는 방법들이 연구되고 있다. 차상중심의 위치검지방식은 열차의 위치, 속도, 시각정보를 연속적으로 측정하여 열차의 제어정보로 사용하는 방식이다. 이러한 차상중심의 위치검지방식은 무선기반 열차제어 및 자기부상열차제어와 같이 궤도회로의 사용을 최소화 하는 최근 열차제어시스템의 개발동향이다. 본 논문에서는 GPS항법 및 DR항법의 특징을 분석하고 GPS항법과 DR항법의 단점을 보완하는 구조를 가지는 GPS/DR기반의 차상열차위치검지방식을 제안하였다. 항법오차의 추정자로서 3차윈 위치 오차, 자세각 오차, 타코메타 환산계수 오차를 상태변수로 하는 5차 칼만필터를 사용하여 최적의 위치오차 및 DR항법용 센서의 오차 추정이 가능하도록 필터를 설계하였으며 모의시험을 통해 GPS/DR기반의 차상열차위치검지장치의 위치추정성능을 확인하였다.

• Journal of Positioning, Navigation, and Timing
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• 제4권3호
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• pp.123-130
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• 2015

In this study, a carrier smoothed global positioning system / dead reckoning (CSGPS/DR) integrated system for high-precision trajectory estimation for the purpose of vehicle navigation was proposed. Existing code-based GPS has a low position accuracy, and carrier-phase differential global positioning system (CPDGPS) has a long waiting time for high-precision positioning and has a problem of high cost due to the establishment of infrastructure. To resolve this, the continuity of a trajectory was guaranteed by integrating CSGPS and DR. The results of the experiment indicated that the trajectory precision of the code-based GPS showed an error performance of more than 30cm, while that of the CSGPS/DR integrated system showed an error performance of less than 10cm. Based on this, it was found that the trajectory precision of the proposed CSGPS/DR integrated system is superior to that of the code-based GPS.

• ETRI Journal
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• 제34권3호
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• pp.379-387
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• 2012

In this paper, an error compensation technique for a dead reckoning (DR) system using a magnetic compass module is proposed. The magnetic compass-based azimuth may include a bias that varies with location due to the surrounding magnetic sources. In this paper, the DR system is integrated with a Global Positioning System (GPS) receiver using a finite impulse response (FIR) filter to reduce errors. This filter can estimate the varying bias more effectively than the conventional Kalman filter, which has an infinite impulse response structure. Moreover, the conventional receding horizon Kalman FIR (RHKF) filter is modified for application in nonlinear systems and to compensate the drawbacks of the RHKF filter. The modified RHKF filter is a novel RHKF filter scheme for nonlinear dynamics. The inverse covariance form of the linearized Kalman filter is combined with a receding horizon FIR strategy. This filter is then combined with an extended Kalman filter to enhance the convergence characteristics of the FIR filter. Also, the receding interval is extended to reduce the computational burden. The performance of the proposed DR/GPS integrated system using the modified RHKF filter is evaluated through simulation.