• Journal of Institute of Control, Robotics and Systems
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• v.6 no.10
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• pp.928-935
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• 2000

In order to improve the performance of a GPS/DR integration system, the error sources of DR sensors should be modeled accurately, This results in the increases in the dimension of the integration filter and, consequently, computational load becomes large. To reduce the computational load, suggested in this paper is a decoupled GPS/DR integration scheme that consists of two cascaded Kalman filters. The GPS velocity output is used in the first filter to calibrate the DR sensor and to fix the velocity as well. The velocity from the first filter is fed to the second filter where the position is corrected using the GPS position output. Experimental results show that the proposed integration scheme has positioning performance comparable to the conventional coupled one, while its computation is reduced to about 2/3.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.478-481
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• 1996

Tracking a target of versatile maneuver recently demands a stable adaptation of tracker, and the multiple model techniques are being developed because of its ability to produce useful information of target maneuver. This paper presents the way to apply the multiple model method in a moving-target and moving-platform scenario, and the estimation and prediction results better than those of single Kalman filter.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.125-130
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• 1991

This paper presents a tracking filter using pseudomeasurements in an estimated line-of-sight Cartesian coordinate system(ELCCS) whose x-axis is on the line-of-sight to an estimated target position. A target dynamics model and a measurement equation in the ELCCS are derived first and then a tracking filter in the ELCCS named moving coordinate tracking filter(MCTF) is proposed. It is shown that this MCTF is equivalent to a Kalman filter in the inertial Cartesian coordinate system which is widely used in the target tracking system. By approximating the MCTF for a pseudomeasurement noise and an error covariance matrix in the ELCCS, decoupling of three axes can be achieved. In this case, named decoupled moving coordinate tracking filter(DMCTF), computation time can be drastically reduced by utilizing its parallel structure. Finally, the stochastic properties of the MCTF and DMCTF are presented. Especially, a sufficient condition of nondestabilizing deviation for the DMCTF is proposed. The performance of the MCTF and DMCTF are compared with a conventional Kalman tracking filter.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2311-2313
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• 2000

In this paper, we consider $H^{\infty}$ optimal Kalman filter problems for linear weakly coupled stochastic systems. We introduce a decomposition for the systems of the Hamiltonian form, which plays an important role of exclusion of ill-condition by ${\varepsilon}$-effect and the parallel computation possibility. It is shown that the algebraic Riccati equation of the weakly coupled $H^{\infty}$ optimal Kalman filter problem is decoupled into completely independent reduced-order, well-defined, two suboptimal Kalman filters.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.967-976
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• 2016

This paper presents a 3D carrier-smoothed GNSS/DR (Global Navigation Satellite System/Dead Reckoning) integrated system for precise ground-vehicle trajectory estimation. For precise DR navigation on sloping roads, the AHRS (Attitude Heading Reference System) methodology is employed. By combining the integrated carrier phase of GNSS and DR sensor measurements, a vehicle trajectory with an accuracy of less than 20cm is obtained even when cycle slip or change of visibility occur. In order to supplement the weak GNSS environment with DR successfully, the DR sensor is precisely compensated for using GNSS Doppler measurements when GNSS visibility is good. By integrating a multi-GNSS receiver with low-cost IMU, a precise 3D navigation system for land vehicles is proposed in this paper. For real-time implementation, a decoupled Kalman filter is employed in the integrated system. Through field experiments, the performance of the proposed system is verified in various road environments, including sloping roads, good-visibility areas, high multi-path areas, and under-ground parking areas.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.270-276
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• 2002

An integrated robust fault diagnosis and fault accommodation strategy for a class of linear stochastic systems subjected to unknown disturbances is presented under the assumption that only a single fault may occur at a given time. The strategy is based on the fault isolation and estimation using a bank of robust two-stage Kalman filters and introduction of the additive compensation input for cancelling out the fault's effect on the system. Each filter is set up such that the residual is decoupled from unknown disturbances and fault with the influence vector designed in the filter. Simulation results for the simplified longitudinal flight control system with parameter uncertainties, process and sensor noises demonstrate the effectiveness of the present approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.1 s.24
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• pp.5-12
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• 2006

This study describes an SDINS/GPS/ZUPT integration algorithm for land navigation systems. The SDINS error can be decoupled in two parts. The first part is the the Schuler component which does not depend on object motion parameters, and the other is the Non-Schuler part which depends on the product of object acceleration and azimuth error. Azimuth error causes SDINS error in proportion to the traversed distance. The proposed system consists of a GPS/SDINS integration system and an SDINS/ZUPT integration system, which are both realized by an indirect feedforward Kalman filter. The main difference between the two is whether the estimate includes the Non-Schuler error or not, which is decided by the measurement type. Consequently, subtracting GPS/SDINS outputs from SDINS/ZUPT outputs provide the Non-Schuler error information which can be applied to improving azimuth accuracy. Simulation results using the raw data obtained from a van test attest that the proposed SDINS/GPS/ZUPT system is capable of providing azimuth improvement.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.50-58
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• 2009

For precise tracking control of a servo system with nonlinear friction, a robust friction compensation scheme is presented in this paper. The nonlinear friction is difficult to identify the friction parameters exactly through experiments. Friction parameters can be also varied according to contact conditions such as the variation of temperature and lubrication. Thus, in order to overcome these problems and obtain the desired position tracking performance, a robust adaptive back-stepping control scheme with a dual friction observer is developed. In addition, to estimate lumped friction uncertainty due to modeling errors, a DEKF recurrent neural network and adaptive reconstructed error estimator are also developed. The feasibility of the proposed control scheme is verified through the experiment fur a ball-screw system.