• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.11
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• pp.1079-1086
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• 2008

During transfer alignment navigation information transferred MINS(master inertial navigation system) to SINS(slave inertial navigation system) has a changed time delay. The changed time delay degrades the performance of transfer alignment. This paper proposes an adaptive filter that estimates covariance of a time delay in real-time using residual of measurements. The performance of the adaptive filter is compared with that of the EKF(extended Kalman filter) in case of transfer alignment for vertical launcher in the ship. The results show that proposed method is more effective than EKF in estimating attitude errors.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.72-78
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• 2007

Determination of the local vertical is not trivial for a moving vehicle and in general will require corrections for the Earth geophysical deflection. The vehicle's local vertical can be estimated by INS integration with initial alignment in SDINS(Strap Down INS) system. In general, the INS has drift error and it cause the performance degradation. In order to compensate the drift error, GPS/INS augmented system is widely used. And in the event that GPS is denied or unavailable, celestial navigation using star tracker can be a backup navigation system especially for the military purpose. In this celestial navigation system, the vehicle's position determination can be achieved using more than two star trackers, and the accuracy of position highly depends on accuracy of local vertical direction. Modern tilt sensors or accelerometers are sensitive to the direction of gravity to arc second(or better) precision. The local gravity provides the direction orthogonal to the geoid and, appropriately corrected, toward the center of the Earth. In this paper the relationship between direction of center of the Earth and actual gravity direction caused by geophysical deflection was analyzed by using precision orbit simulation program embedded the JGM-3 geoid model. And the result was verified and evaluated with mathematical gravity vector model derived from gravitational potential of the Earth. And also for application purpose, the performance variation of pure INS navigation system was analyzed by applying precise gravity model.

• Journal of Ocean Engineering and Technology
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• v.31 no.2
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• pp.164-169
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• 2017

Studies were performed on an ARS using SDINS's RLG and the geomatic sensor. To develop the ARS, experiments were performed to determine the characteristics of the RLG and geomatic sensor. Based on the results, to reduce the angular position errors of the RLG, which accumulate from the angular velocity data, an algorithm was studied that uses the Extended Kalman filter (EKF) to compensate the RLG data and geomatic sensor data. To verify the performance of the developed algorithm for reducing the cumulative angular errors, experiments that included the developed EKF were performed. Through these, it was shown that a drastic reduction in the angular errors of the RLG were achieved.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.543-549
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• 2021

In this paper, a robust transfer alignment method is proposed for a strapdown inertial navigation system(SDINS) with norm-bounded parametric uncertainties. The uncertainties are described by the energy bound constraint, i.e., sum quadratic constraint(SQC). It is shown that the SQC can be coverted into an indefinite quadratic cost function in the Krein space. Krein space Kalman filter is designed by modifying the measurement matrix and the variance of measurement noises in the conventional Kalman filter. Since the proposed Krein space Kalman filter has the same recursive structure as a conventional Kalman filter, the proposed filter can easily be designed. The simulation results show that the proposed filter achieves robustness against measurement time delay and high dynamic environment of the vehicle.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1868-1878
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• 2016

This paper proposes a novel velocity estimator for long-term underwater navigation of autonomous underwater vehicles(AUVs). Provided that an external position fix is not given, a viable goal in designing a underwater navigation algorithm is to reduce the divergence rate of position error only using the sporadic velocity information obtained from Doppler velocity log(DVL). For such case, the performance of underwater navigation eventually depends on accuracy and reliability of external velocity information. This motivates us to devise a velocity estimator which can drastically enhance the navigation performance even when the DVL measurement is unavailable. Incorporating the Gertler-Hagen hydrodynamics model of an AUV with the measurement models of velocity and depth sensors, the velocity estimator design problem is resolved using the extended Kalman filter. Different from the existing methods in which an AUV simulator is regarded as a virtual sensor, our approach is less sensitive to the model uncertainty often encountered in practice. This is because our velocity filter estimates the simulator errors with sensor aids and furthermore compensates these errors based on the indirect feedforward manner. Through the simulations for typical AUV navigation scenarios, the effectiveness of the proposed scheme is demonstrated.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.109-117
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• 2010

With the advent of new technologies such as HSDPA, WiBro(Wireless Broadband) and personal devices, we can access various contents and services anytime and anywhere. A location based service(LBS) is essential for providing personalized services with individual location information in ubiquitous computing environment. In this paper, we propose mapping algorithm for error compensation of indoor localization system. Also we explain filter and indoor localization system. we have developed mapping algorithms composed of a map recognition method and a position compensation method. The map recognition method achieves physical space recognition and map element relation extraction. We improved the accuracy of position searching. In addition, we reduced position errors using a dynamic scale factor.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.4
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• pp.71-80
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• 2006

Strapdown Inertial navigation systems consist of an inertial sensor assembly(ISA), electronic modules to process sensor data, and a navigation computer to calculate attitude, velocity and position. In the ISA, most gryoscopes such as RLGs and FOGs, have digital output, but typical accelerometers use current as an analog output. For a high precision inertial navigation system, sufficient stability and resolution of the accelerometer board converting the analog accelerometer output into digital data needs to be guaranteed. To achieve this precision, the asymmetric error and A/D reset scale error of the accelerometer board must be properly compensated. If the relation between the acceleration error and the errors of boards are exactly known, the compensation and estimation techniques for the errors may be well developed. However, the A/D Reset scale error consists of a pulse-train type term with a period inversely proportional to an input acceleration additional to a proportional term, which makes it difficult to estimate. In this paper, the effects on the acceleration output for auto-pilot situations and the effects of A/D reset scale errors during horizontal alignment are qualitatively analyzed. The result can be applied to the development of the real-time compensation technique for A/D reset scale error and the derivation of the design parameters for accelerometer board.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.2
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• pp.189-196
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• 2019

The inertial sensor errors in SDINS(Strapdown Inertial Navigation System) can be compensated by rotating the inertial measurement unit and it is called RINS(Rotational Inertial Navigation System). It is assumed that the error of the inertial sensor in RINS is a static bias. However, the error of the inertial sensor actually developed and produced is not a static bias due to the change of the temperature applied to the sensor and the influence of the earth's gravity acceleration. In this paper, we propose a six-position gyro bias calibration method to evaluate the gyro bias required for RINS and present the test results of applying it to a ring laser gyro inertial navigation system under development.