• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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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.