• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.6
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• pp.577-590
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• 2021

In this paper, we theoretically analyzed the self-alignment/navigation performance in the accelerometer resonance state generated by dither motion of ring laser gyroscope in LINS and verified it through simulation. As a result of analysis, it is confirmed that the amplitude of the accelerometer measurement amplified in the accelerometer resonance state is decreased in the process of sampling per the navigation calculation period and that frequency is changed by the aliasing effect too. It was also analysed that the attitude error in self-alignment is determined by the amplitude/frequency of the accelerometer measurement, the gain of the self-alignment loop, and the velocity and position error in the navigation is determined by the amplitude/frequency/phase error of the accelerometer measurement. This analysis and simulation results show that the self-alignment and navigation performance is not be degraded only when the amplification factor of the accelerometer measurement in the accelerometer resonance state is 3 or less

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.355-359
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• 2006

For the poor observability of azimuth misalignment angle and east gyro drift rate of the traditional initial alignment, a bran-new SINS stationary fast self-alignment approach is proposed. By means of analyzing the characteristic of the strapdown inertial navigation system (SINS) stationary alignment seriously, the new approach takes full advantage of the specific force and angular velocity information given by inertial measurement unit (IMU) instead of the mechanization of SINS. Firstly, coarse alignment algorithm is presented. Secondly, a new fine alignment model for SINS stationary self-alignment is derived, and the observability of the model is analysed. Then, a modified Sage-Husa adaptive Kalman filter is introduced to estimate the misalignment angles. Finally, some computer simulation results illustrate the efficiency of the new approach and its advantages, such as higher alignment accuracy, shorter alignment time, more self-contained and less calculation.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.4
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• pp.435-442
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• 2016

For inertial navigation systems, initial information such as position, velocity and attitude is required for navigation. Self-alignment is the process to determine initial attitude on stationary condition using inertial measurements such as accelerations and angular rates. The accuracy of self-alignment is determined by inertial sensor error. As soon as an inertial navigation system is powered on, the temperature of accelerometer rises rapidly until temperature stabilization. It causes acceleration error which is called temperature stabilizing error of accelerometer. Therefore, temperature stabilizing error degrades the alignment accuracy and also increases alignment time. This paper suggests a method to calculate azimuthal attitude using curve fitting of horizontal control angular rate in fixed-gain self-alignment. It is verified by simulation and experiment that the accuracy is improved and the alignment time is reduced using the proposed method under existence of the temperature stabilizing error.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.8
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• pp.796-803
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• 2011

It is called self-alignment or initial alignment that INS(Inertial Navigation System) is aligned using the measurements from the inertial sensors as an accelerometer and a gyroscope and the inserted reference navigation information in the stop state. The main purpose of self-alignment is to obtain the initial attitude of INS. The accuracy of self-alignment is determined by the performance grade of the used inertial sensors, especially horizontal attitude accuracy by the horizontal accelerometer and vertical attitude accuracy by the E-axis gyroscope. Therefore the uncertain errors in the inertial sensors cause the performance of self-alignment to degrade. In this paper, we analyze theoretically and through a simulation how the errors of inertial sensors in the temperature stabilizing state, one of the uncertain errors, affect the accuracy of self-alignment.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.708-715
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• 2010

In Strapdown Inertial Navigation System, alignment accuracy is the most important factor to determine the performance of navigation. However by an existing self-alignment method, it takes a long time to acquire the alignment accuracy that we want. So, to attain the desired alignment accuracy in as little as $\bigcirc$ minutes, we have developed the precise multi-position alignment method. In this paper, it is proposed a inertial measurement matching transfer alignment method among alignment methods to minimize the alignment error in a short time. It is based on a mixed velocity-DCM matching method be suitable to the operating environment of vertical launching system. The compensation methods to reduce misalign error, especially azimuth angle error incurred by measurement time-delay error and body flexure error are analyzed and evaluated with simulation. This simulation results are finally confirmed by experimentations using FMS(Flight Motion Simulator) in Lab and the integration test to follow the fire control mission.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.6
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• pp.463-472
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• 2017

Inertial Navigation System Alignment is the process to determine direction cosine matrix which is the transformation matrix between the INS body frame and navigation frame. INS initial position value is necessary to INS attitude calculation, so that user should wait until he get such value to start the INS alignment. To remove the waiting time, we propose an alignment algorithm that immediately starts after the INS power on by using pseudo initial position input and then is completed with attitude error compensation by entering true position later. We analyse effect of INS sensor error on attitude in process of time and verify the performance and usefulness of the close-loop alignment algorithm which corrects attitude error from the change of initial position.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.56.1-56
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• 2001

Initial attitude error is one of the large error sources in the navigation errors of SDINS. And it is important to decide the initial attitude of SDINS. The method, like a self-alignment or a transfer alignment method, is required to a precise INS. If we do not have a precise INS, we should get large attitude error. After performing the initial alignment, a vehicle has the initial attitude error. Therefore, it results in navigation error due to the initial attitude error. But, if we use position information during flight, we could estimate and compensate a vehicle attitude error. So, we can maintain a precise attitude in spite of existing the initial attitude error. Using the uplinked position information from a land-based radar system, the new algorithm estimates the attitude of the SDINS during flight ...

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.990-994
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• 2003

When the low cost IMU is used, the result of the stationary self alignment is not suitable for navigation. In this paper, an in-motion alignment method is proposed to obtain an accurate initial attitude of a low cost IMU based GPS/INS integration system. To design Kalman filter for alignment, large heading error model is introduced. And then Kalman filter is designed to estimate initial attitude error as the indirect feedback filter. In order to assess performance of the alignment method, computer simulations are carried out. The simulation results show that initial attitude error rapidly reduces.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.86-94
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• 2002

The initial alignment of inertial platform for navigation system was considered. An adaptive filtering technique is developed for the system with unknown and varying sway disturbance. It is assumed that the random sway motion is the second order ARMA(Auto Regressive Moving Average) model and performed parameter identification for unknown parameters. Designed adaptive filter contain both a Kalman filter and a self-tuning filter. This filtering system can automatically adapt to varying environmental conditions. To verify the robustness of the filtering system, the computer simulation was performed with unknown and varying sway disturbance.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.536-541
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• 2004

It is important to estimate and calibrate sensor errors in maintaining the performance level of SDINS. In this study, an estimation technique of fixed sensor errors for SDINS calibration is discussed. First, the fixed errors of gyros and accelerometers, excluding gyro biases are estimated by the navigation information of SDINS in multi-position. The SDINS with RLG includes flexure errors. In this study, the gyros flexures are out of consideration, but the proposed procedure selects certain positions and rotations in order to minimize the influence of flexures. Secondly, the influences of random walks, flexures and orientation errors are verified via numerical simulations. Thirdly, applying the previous estimated errors to SDINS, the estimation of gyro biases is conducted via the additional control signals of close-loop self-alignment. Lastly, the experiments illustrate that the extracted calibration parameters are available for the improvement of SDINS.