• Journal of Institute of Control, Robotics and Systems
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• v.14 no.6
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• pp.595-602
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• 2008

In this paper, performance of the initial alignment for INS whose attitude is not leveled is investigated. Observability of the initial alignment filter is analyzed and estimation errors of the estimated state variables are derived. First, the observability is analyzed using the rank test of observability matrix and the normalized error covariance of the Kalman filter based on the 10-state model. In result, it can be seen that the accelerometer biases on horizontal axes are unobservable. Second, the steady-state estimation errors of the state variables are derived using the observability equation. It is verified that the estimates of the state variables have errors due to the unobservable state variables and the non-leveling tilt angles of a vehicle containing the INS. Especially, this paper shows that the larger the tilt angles of the vehicle are, the larger the estimation errors corresponding to the sensor biases are. Finally, it is shown that the performance of the 8-state model excepting the accelerometer biases on horizontal axes is better than that of the 10-state model in the initial alignment by simulation.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.493-495
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• 2015

PDR은 일반적으로 IMU센서로 부터의 가속도와 각속도를 측정하여 보행자의 위치를 추적하는 시스템이다. IMU센서로부터 측정된 가속도와 각속도 값은 센서를 기준으로 하기 때문에 보행자가 인지하는 고정 좌표계와는 차이가 있다. 이를 해결하기 위해 회전행렬을 사용하며 이후 계속해서 측정되는 각속도를 통해 회전행렬을 업데이트 한다. 업데이트된 회전행렬을 통해 좌표계를 환산하고 환산된 좌표계의 가속도 값으로부터 보행자는 고정좌표계 기준으로 위치 추적이 가능하다. 하지만 회전행렬을 업데이트 하는 과정에서 센서의 세 축이 이상적으로 수직이 아니라면 업데이트 과정에서 각속도의 오차가 누적되고 이는 좌표계를 환산에 영향을 끼쳐 위치 및 속도 추적 정확성을 낮춘다. 물리적인 Bias가 PDR 시스템에 누적오차를 발생시킨다. 이에 제안하는 센서 축 편향 보정 알고리즘은 IMU 센서의 물리적 축 오차를 보정해주어 더 정확한 위치 추적을 가능하게 한다. 또한 Matlab을 통해 데이터를 분석하고 알고리즘의 필요성을 보인다.

• Aerospace Engineering and Technology
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• v.7 no.1
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• pp.142-150
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• 2008

In order to ensure the individual and mutual performances among the telemetry system, tracking system, flight termination system, GPS, and inertial navigation & guidance system which are installed in the KSLV-I 2nd stage and ground equipment of the Naro space center, flight test using a light airplane is required. Since the high degree of test efficiency is fulfilled through the minute plan and analysis about selection of the equipment which are applicable to the test, harness, operation strategy, and antenna installation. KSLV-I communication environment and flight profile should be precisely taken into account during the flight test. In this document, overall aspect of the KSLV-I 2nd stage equipment specification, a rack for the installation, harness, the airplane specification, and flight route which are required for the effective flight test are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.8
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• pp.703-710
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• 2001

The nonlinear observers are proposed for a nonlinear system. To improve the characteristics such as stability, convergence, and $H^{\infty}$ filter performance criterion, we utilize an $H^{\infty}$ filter Riccati equation or a modified $H^{\infty}$ filter Riccati equation with a freedom parameter. Using the Lyapunov function method, the characteristics of the observers are analyzed. Then the in-flight alignment for a strapdown inertial navigation system(SDINS) is designed using the proposed observer. And the additive quaternion error model is especially used to reduce the uncertainty of the SDINS error model. Simulation results show that the observer with the modified $H^{\infty}$ filter Riccati equation effectively improves the performance of the in-flight alignment.

• Journal of Ocean Engineering and Technology
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• v.18 no.4 s.59
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• pp.33-39
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• 2004

This paper presents a hybrid underwater navigation system for unmanned underwater vehicles, using an additional range sonar, where the navigation system is based on inertial and Doppler velocity sensors. Conventional underwater navigation systems are generally based on an inertial measurement unit (IMU) and a Doppler velocity log (DVL), accompanying a magnetic compass and a depth sensor. Although the conventional navigation systems update the bias errors of inertial sensors and the scale effects of DVL, the estimated position slowly drifts as time passes. This paper proposes a measurement model that uses the range sonar to improve the performance of the IMU-DVL navigation system, for extended operation of underwater vehicles. The proposed navigation model includes the bias errors of IMU, the scale effects of VL, and the bias error of the range sonar. An extended Kalman filter was adopted to propagate the error covariance, to update the measurement errors, and to correct the state equation, when the external measurements are available. To illustrate the effectiveness of the hybrid navigation system, simulations were conducted with the 6-d.o.f. equations of motion of an AUV in lawn-mowing survey mode.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1417-1423
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• 2020

This paper proposes a waypoint guidance algorithm for the Autonomous Underwater Vehicle(AUV). The proposed simplified guidance algorithm is presented, which is combined LOS guidance and cross-track guidance for path following. Cross-track error is calculated using the position of the AUV and reference path. LOS guidance and cross-track guidance are appropriately changed according to cross-track error. And the stability of the system has been improved using variable cross-track control gain by cross-track error. Also, in this paper, navigation hardware in-the loop simulation(HILS) is implemented to verify navigation algorithm of AUV that performs combined navigation using inertial navigation device and doppler velocity log(DVL). Finally, we design integrated system HILS (including navigation HILS) for performance verification of guidance algorithm of the autonomous underwater vehicle. By comparing the sea test result with HILS result, the proposed guidance algorithm and HILS configuration were confirmed be correct.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.843-848
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• 2001

Most of gimballed inertial navigation systems(GNIS) are calibrated periodically to maintain their inherent accuracy. The existing calibration techniques using the conventional schuler test with the least square method and the multiposition test take a long time and have some problems in procedures. To solve this problem, calibration method using a linear Kalman filter is proposed by us. In this paper, the calibration method by the change of Schuler period is studied in order to improve the calibration performance of the gimballed INS. First of all, it is shown that the observability of Kalman filter is also enhanced the Schuler period is decreased. Simulation results show that the calibration performance using the present scheme is improved according to the decrease of the Schuler period and the calibration time is shortened extremely, too. And our proposed technique shows desirable estimation performance for the g-sensitive errors of inertial sensors in particular.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.468-473
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• 2014

This paper describes the in-flight alignment of SDINS (Strapdown Inertial Navigation Systems) using an EKF (Extended Kalman Filter) and a UKF (Unscented Kalam Filter), which allow large initial attitude error uncertainty. Regardless of the inertial sensors, there are nonlinear error dynamics of SDINS in cases of large initial attitude errors. A UKF that is one of the nonlinear filtering approaches for IFA (In-Flight Alignment) are used to estimate the attitude errors. Even though the EKF linearized model makes velocity errors when predicting incorrectly in case of large attitude errors, a UKF can represent correctly the velocity errors variations of attitude errors with nonlinear attitude error components. Simulation results and analyses show that a UKF works well to handle large initial attitude errors of SDINS and the alignment error attitude estimation performance are quite improved.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.691-698
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• 2015

Inertial Navigation Systems (INS) are widely used as the main navigation device for aircraft. To get the initial attitude, the INS requires the initial alignment before navigation starts. An aircraft also needs an engine test procedure that causes some vibrations before flight. An INS can't be aligned in a vibration environment so the initial alignment is performed before the aircraft engine test. Therefore, the initial alignment time of an INS has been a major factor in limiting an aircraft's takeoff response time. In this paper, we designed an initial alignment algorithm that can be executed even in disturbances such as aircraft run-up. We demonstrated verification of the algorithm that is embedded on the real INS and testing methods to evaluate the alignment of the INS. We also analyzed the test results of the proposed initial alignment algorithm that is performed during a real aircraft run-up.

• Journal of Ocean Engineering and Technology
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• v.19 no.6 s.67
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• pp.78-85
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• 2005

Initial alignment and localization are important topics in inertial navigation systems, since misalignment and initial position error wholly propagate into the navigation systems and deteriorate the performance of the systems. This paper presents the error convergence characteristics of the hybrid navigation system for underwater vehicles initial position, which is based on an inertial measurement unit (IMU) accompanying a range sensor. This paper demonstrates the improvement on the navigational performance oj the hybrid system with the range information, especially focused on the convergence of the estimation of underwater vehicles initial position error. Simulations are performed with experimental data obtained from a rotating ann test with a fish model. The convergence speed and condition of the initial error removal for random initial position errors are examined with Monte Carlo simulation. In addition, numerical simulation is conducted with an AUV model in lawn-mowing survey mode to illustrate the error convergence of the hybrid navigation System for initial position error.