• 한국해양공학회지
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• 제19권6호통권67호
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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.

• 제어로봇시스템학회논문지
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• 제14권6호
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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.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.97-108
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• 2020

This paper compares several methods for estimating parameters of normal inverse Gaussian distribution. Ordinary maximum likelihood estimation and the method of moment estimation often do not work properly due to restrictions on parameters. We examine the performance of adjusted estimation methods along with the ordinary maximum likelihood estimation and the method of moment estimation by simulation and real data application. We also see the effect of the initial value in estimation methods. The simulation results show that the ordinary maximum likelihood estimator is significantly affected by the initial value; in addition, the adjusted estimators have smaller root mean square error than ordinary estimators as well as less impact on the initial value. With real datasets, we obtain similar results to what we see in simulation studies. Based on the results of simulation and real data application, we suggest using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values to estimate the parameters of normal inverse Gaussian distribution.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1768-1769
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• 2011

The nonlinear estimation and the pseudo-linear estimation are used to treat the target localization in sensor network which provides range difference of arrival (RDOA) measurements. It is known that the nonlinear estimation has sensitive problem for the initial estimate and the pseudo-linear estimation has a large estimation error. The QCLS method is the typical estimator of the methods for pseudo-linear estimation. However the estimate by using the QCLS method includes the estimation error because the first stage of two estimation processes of the QCLS method causes the biased estimation error. Therefore we propose a instrumental variables(IV) method for minimizing the estimation error of the first stage. The simulation shows that the performance of the proposed method is superior to the QCLS method.

• International Journal of Aeronautical and Space Sciences
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• 제12권1호
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• pp.24-36
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• 2011

A new approach for spacecraft absolute attitude estimation based on the unscented Kalman filter (UKF) is extended to relative attitude estimation and navigation. This approach for nonlinear systems has faster convergence than the approach based on the standard extended Kalman filter (EKF) even with inaccurate initial conditions in attitude estimation and navigation problems. The filter formulation employs measurements obtained from a vision sensor to provide multiple line(-) of(-) sight vectors from the spacecraft to another spacecraft. The line-of-sight measurements are coupled with gyro measurements and dynamic models in an UKF to determine relative attitude, position and gyro biases. A vector of generalized Rodrigues parameters is used to represent the local error-quaternion between two spacecraft. A multiplicative quaternion-error approach is derived from the local error-quaternion, which guarantees the maintenance of quaternion unit constraint in the filter. The scenario for bounded relative motion is selected to verify this extended application of the UKF. Simulation results show that the UKF is more robust than the EKF under realistic initial attitude and navigation error conditions.

• 한국항행학회논문지
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• 제26권4호
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• pp.235-243
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• 2022

본 논문에서는 관성 항법 시스템 (INS)의 경우, 수직편향 (DOV)으로 인한 초기정렬에서의 자세 추정 오차를 분석한다. INS의 속도 및 자세 오차를 기반으로 DOV로 인한 자세 추정 오차를 이론적으로 분석하였다. 이론적 분석을 검증하기 위한 시뮬레이션을 수행했으며 결과는 이론적 분석과 잘 일치했다. 일례로 η=20"일 경우 정렬오차는 ϕ_N=0.00287°, ϕ_U=0.00196°가발생하며, 𝜉=20"일 경우에는 ϕ_E= -0.00286°의 오차가 발생하였다. 이를 통해 INS 자세오차의 결합특성으로 DOV에 기인한 수직 자세오차가 발생함을 확인하였다. 기존의 INS 정렬에서는 고려하지 않았던 DOV로 인해 추가로 자세오차가 발생할 수 있음을 보여 주었으며 이는 고정밀 INS 적용시에 DOV에 대한 보정을 반드시 고려해야 함을 의미한다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2003년도 추계학술대회 논문집
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• pp.104-108
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• 2003

This paper explained algorithm for a initial pole position estimation of a permanent magnet linear synchronous motor(PMLSM). Generally this motor is considered initial pole position with a position sensor such as incremental encoder for the precise initial pole position estimation and high performance. But this is based on the principle that the initial pole position is accomplished by the PI controller using the maximum values of a position error generated by the new proposed two reference frames and also by using a rated force for input. the proposed algorithm does not utilize the general methods such as impedance ratio, EMF and using the magnetic saturation. In other words, this can be applied without respect to variety of the motor structure because of insensitivity to the motor parameters. In conclusion, simulation results are presented to confirm performance of initial pole position estimation method.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2006년도 춘계학술발표회 논문집(I)
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• pp.506-509
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• 2006

Extended Kalman Filter iterate the prediction and the filtering based on Initial state for the next time step. EKF method for the estimation of nonlinear parameters of a structural dynamic system is necessary that initial of state vector and error covariance matrix. Because those are unknown exactly, generally selected random values. That occasion observability problem appear because of unknown initial values. In this study, for the estimation of the nonlinear parameters, a simple one degree of Freedom example is carried out by Extended Kalman Filter. And initial value assumption for Parameter Estimation of Dynamic System are developed. The result of analysis is compared with calculated standard values.

• 한국군사과학기술학회지
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• 제5권2호
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• pp.185-194
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• 2002

본 논문에서는 jammer를 향하여 호밍하는 대함 유도탄에 대하여 적용할 수 있는 피동 거리추정필터를 제안하였다. 최근의 jammer는 상당히 먼 거리에서 jamming이 가능하므로, 제안된 필터는 필터 초기치 오차가 큰 경우에도 이를 신속히 제거하고 잘 동작할 수 있도록 설계되었다. 함대함 유도탄의 경우, 표적에 비하여 유도탄의 운동이 훨씬 주도적이므로 교전상황은 상대거리와 시선변화율을 상태변수로 하는 2차 시스템으로 모델링이 가능하다. 본 논문에서는 이와같은 2차 모델에 근거한 확장칼만필터를 구성하고, 최소자승법을 이용한 초기치 오차 추정 알고리듬을 부가함으로써 새로운 피동 거리추정필터를 유도하였다. 제안된 필터는 필터의 초기치 오차가 상당히 큰 경우에도 적은 계산량으로 우수한 거리추정성능을 보여주었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1694-1700
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• 2004

In this paper, we propose the AWLS/MFT (Adaptive Weighed Least Squares/ Modulation Function Technique) devised by A. E. Pearson et al. for the transfer function estimation of a modal system and investigate the performance of several algorithms, the Gram matrix method, a Luenberger Observer (LO), Least Squares (LS), and Recursive Least Squares (RLS), for the estimation of initial conditions. With the benefit of the Modulation Function Technique (MFT), we can separate the estimation problem into two phases: the transfer function parameters are estimated in the first phase, and the initial conditions are estimated in the second phase. The LO method produces excellent IC estimates in the noise free case, but the other three methods show better performance in the noisy case. Finally, we compared our result with the Prony based method. In the noisy case, the AWLS and one of the three methods - Gram matrix, LS, and RLS- show better performance in the output Signal to Error Ratio (SER) aspect than the Prony based method under the same simulation conditions.