• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.409-409
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• 2000

In this paper, the implementation of a tightly coupled real-time GPS/INS integrated system is discussed. The hardware is developed for any GPS receiver and any IMU. The navigation software is modularized by tasks, so that can be easily modified when the integrated system is restructured. A van test was performed to show the feasibility of the proposed system.

• 한국군사과학기술학회지
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• 제11권4호
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• pp.116-123
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• 2008

In this paper we study the performance of the measurement time-delay estimation of tightly-coupled GPS/INS(Global positioning system/Inertial Navigation system) system. Generally, the heading error estimation performance of loosely-coupled GPS/INS system using GPS's Navigation Solution is poor. In the case of tightly-coupled GPS/INS system using pseudo-range and pseudo-range rate, the heading error estimation performance is better. However, the time-delay error on the measurement(pseudo-range rate) make the heading error estimation performance degraded. So that, we propose the time-delay model on the measurement and compose the time-delay estimator. And we confirm that the heading error estimation performance in the case of measurement time-delay existence is similar with the case of no-delay by Monte-Carlo simulation.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.785-791
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• 2008

Ultra-tightly coupled GPS/INS integration has been reported to show better navigation performance than that of other integration methods such as loosely coupled and tightly coupled integration. This paper uses the particle filter for ultra-tightly coupled GPS/INS integration and analyzes the navigation performance according to vehicle trajectory and the number of particles. The navigation performance of particle filter is compared with those of EKF and UKF.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.822-825
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• 1999

This paper compares two methods of GPS/INS integration ; tightly-coupled integration ana loosely-coupled integration. In the tightly -coupled method an integrated Kalman filter is designed to process raw GPS measurement data for state update and INS data for propagation. The loosely-coupled integration method uses the solution outputs from a stand-alone GPS receiver for update. The loosely-coupled method is simpler and can readily be applied to off-the-self receivers and sensors while the tightly-coupled integration requires access to raw measurement mechanism of the receiver. Simulation result show that the tightly-coupled integration system exhibits better performance and robustness than loosely-coupled integration method.

• 제어로봇시스템학회논문지
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• 제12권8호
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• pp.780-788
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• 2006

This paper deals with INS/GPS tightly coupled integration algorithms using extend Kalman filter (EKF) and unscented Kalman filter (UKF). In the tightly coupled approach, nonlinear pseudorange measurement models are used for the INS/GPS integration Kalman filter. Usually, an EKF is applied for this task, but it may diverge due to poor functional linearization of the nonlinear measurement. The UKF approximates a distribution about the mean using a set of calculated sigma points and achieves an accurate approximation to at least second-order. We introduce the generalized scaled unscented transformation which modifies the sigma points themselves rather than the nonlinear transformation. The generalized scaled method is used to transform the pseudo range measurement of the tightly coupled approach. To compare the performance of the EKF- and UKF-based tightly coupled approach, real van test and simulation have been carried out with feedforward and feedback indirect Kalman filter forms. The results show that the UKF and EKF have an identical performance in case of the feedback filter form, but the superiority of the UKF is demonstrated in case of the feedforward filer form.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.94-94
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• 2000

In this paper, the performance of INS/GPS integration is analyzed. Generally the integration method is classified into two method. One is loosely coupled integration, Another is tightly coupled integration. For the simulation, the error model of Kalman fitter is defined and the result of simulation is analyzed. When the number of visible satellites is less than four, the error of tightly coupled integration is smaller than that of loosely coupled integration. To very the result of simulation, van test that use LP-81 IMU and Millen3151R GPS receiver is carried out.

• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.817-823
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• 2007

GPS and INS can be integrated in 3 ways of loose, tight, and ultra-tight configuration. This paper investigates the performance of GPS/INS ultra-tightly integrated system when unscented Kalman filter(UKF) is adopted as well as extended Kalman filter(EKF). Covariance analysis is performed using UFK and EKF for tightly coupled and ultra-tightly coupled systems. Various trajectories such as straight, circle, S-shape, spiral are considered for the simulations of covariance analysis.

• 한국군사과학기술학회지
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• 제14권1호
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• pp.49-54
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• 2011

This paper addresses the performance comparisons of the GPS pseudorange and pseudorange rate measurements in the tightly coupled INS/GPS Navigation systems. Even though the two measurements have the same ability in estimating level attitude errors, pseudorange rate has an advantage in improving estimating heading attitude error performance. The performance of pseudorange and pseudorange rate measurements is compared in numerical simulations and van test.

• 한국항행학회논문지
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• 제15권4호
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• pp.536-542
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• 2011

본 논문에서는 GPS/INS 강결합 시스템에서 다중경로 오차에 대한 EKF와 total-state UKF 두 가지 필터의 성능을 비교 분석하였다. 도심 빌딩숲에서 많이 발생하는 다중경로 오차가 없는 경우와 있는 경우에 대하여 시뮬레이션을 수행하였고, 위성이 3개만 보이는 경우에 두 필터의 추정 성능을 비교하였다. 다중경로 오차가 없을 경우보다 있는 경우에 total-state UKF가 EKF에 비하여 더 좋은 추정 성능을 보여서 total-state UKF의 성능이 더 강인함을 확인할 수 있었다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.349-354
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• 2006

For robust INS/GPS navigation system, an efficient multi-filter fusion technique is proposed. In the filtering for nonlinear systems, the representative filter - EKF, and the alternative filters - RHKF filter, SPKF, etc. have individual advantages and weak points. The key concept of the multi-filter fusion is the mergence of the strong points of the filters. This paper fuses the IIR type filter - EKF and the FIR type filter - RHKF filter using the adaptive strategy. The result of the fusion has several advantages over the EKF, and the RHKF filter. The advantages include the robustness to the system uncertainty, temporary unknown bias, and so on. The multi-filter fusion technique is applied to the tightly coupled INS/GPS navigation system and the performance is verified by simulation.