• 한국항공우주학회지
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• 제36권11호
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• pp.1079-1086
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• 2008

관성항법장치 초기정렬 방법인 전달정렬의 경우 MINS에서 SINS로 전송되는 데이터에는 변동하는 시간지연이 존재한다. 이러한 시간지연은 전달정렬의 성능을 저하시킨다. 본 논문에서는 측정치 잉여값을 이용하여 실시간으로 시간지연 공분산값을 추정하여 시간지연 추정오차를 줄이는 적응필터를 제시하고 수직발사 SDINS 전달정렬에 적용하여 확장형 칼만필터의 성능과 비교하였다. 시뮬레이션 결과 배운동이 크게 변할수록 적응필터의 성능이 확장형 칼만필터보다 더 우수한 것으로 나타났다.

• 제어로봇시스템학회논문지
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• 제7권8호
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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.

• 한국항행학회논문지
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• 제24권3호
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• pp.198-204
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• 2020

본 논문에서는 GNSS (global navigation satellite system)이 가용하지 않는 상황에서 시간이 지남에 따라 오차가 누적되는 특성을 가진 관성항법장치(inertial navigation system)의 항법 오차를 보상하기 위한 EM-Log (electromagnetic-log) 보정항법 필터를 설계하였다. EM-Log는 해상에서 운동체의 이동 속도를 측정하여 속도 오차를 보정하여 주나 측정된 속도에는 해조류가 포함되어 있기 때문에 적절한 해조류 모델 설계와 추정이 필요하다. 본 논문에서는 해조류 추정을 위해 단일 모델 필터와 IMM (interacting multiple model) 모델 필터 방법론을 제시하고 설계된 필터의 해조류 추정 성능을 확인한 후 해조류 모델 설계가 필터 성능에 어떤 영향을 주는지 분석하였다. 설계된 보정항법 필터의 성능은 시뮬레이션을 이용하여 검증하고 순수항법 대비 필터 성능 향상률을 비교 분석하였다. 단일 모델 필터는 해조류 모델이 동일한 경우 성능이 좋지만 해조류 모델이 동일하지 않을 경우 성능이 저하되는 것을 확인 할 수 있었다. 반면, IMM 모델 필터의 경우 다양한 해조류 모델을 사용하기 때문에 단일 모델필터 대비 안정적인 성능을 유지하는 것을 확인하였다.

• 전자공학회논문지
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• 제52권5호
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• pp.190-196
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• 2015

본 논문은 항법장치 위치보정을 위해 칼만필터를 적용한 GPS/INS융합의 다중보정방법을 제안한다. 연구에서는 관성항법장치를 구현하기 위해 9축 항법장치로 보정알고리즘을 적용하여 위치오차를 감소시킨 방법을 적용했다. 일반적으로 GPS/INS는 위치정보를 얻어낼 수 있지만 위치정보를 구하는 과정에서 오차 또한 더불어 커지게 되기에 이를 보정하기 위한 강인한 오차 보정 알고리즘이 필요하다. 본 논문에서는 9축 관성센서(mpu-9150)의 외란에 대한 강인성 향상을 위해 가속도계 보정 알고리즘을 사용하여 tilt보정을 수행했으며, 제어 대상체의 정확한 방위를 파악할 수 있도록 Yaw각 재정의 알고리즘을 적용하였다. 최종적으로 GPS/INS와 칼만 필터를 함께 결합한 통합시스템을 구현하였다.

• 한국멀티미디어학회논문지
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• 제24권12호
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• pp.1589-1597
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• 2021

Due to the low output rate and time delay of vehicle's navigation results, the electro-optical tracking system(EOTS) cannot estimate accurate target positions. If an inertial measurement unit(IMU) is additionally mounted into the EOTS and inertial navigation system(INS) is constructed, the high navigation output rate can be obtained. And the time-delay can be compensated by using the augmented Kalman filter. An accurate initial attitude is required in order to have accurate navigation outputs. In this paper, an attitude determination algorithm is proposed using the augmented Kalman filter in order to compensate measurement delay of the EOTS and have accurate initial attitude. The proposed initial attitude determination algorithm consists of an augmented Kalman filter, an INS, and an integrated Kalman filter. The augmented Kalman filter compensates the time-delay of the vehicle's navigation results and the integrated Kalman filter estimates the navigation error of the INS. In order to evaluate performance of the proposed algorithm, vehicle's navigation outputs and IMU measurements were generated using sensors' model-based measurement generator and initial attitude estimation errors of the proposed algorithm and the conventional algorithm without the augmented Kalman filter were compared for the generated measurements. The evaluation results show that the proposed algorithm has better accuracy.

• Advances in aircraft and spacecraft science
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• 제7권1호
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• pp.1-17
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• 2020

In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the changes in the control forces and moments, system dynamics will change too, leading to the failure detection process being encountered with difficulty. To this purpose, an equivalent aerodynamic model is proposed to express the dynamics of the vehicle, and the health of each fin is monitored by the value of a parameter which is estimated using an adaptive robust filter. The proposed method detects and isolates fins damages in a few seconds with good accuracy.

• Journal of Astronomy and Space Sciences
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• 제15권1호
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• pp.229-234
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• 1998

We study on a terrain contour matching algorithm using Radial Basis Functions(RBFs) for aided inertial navigation system for position fixing aircraft, cruise missiles or re-entry vehicles. The parameter optimization technique is used for updating the parameters describing the characteristics of an area with modified Gaussian least square differential correction algorithm and the step size limitation filter according to the amount of updates. We have applied the algorithm for matching a sampled area with a target area supposed that the area data are available from Radar Terrain Sensor(RTS) and Reference Altitude Sensor(RAS)

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.131-135
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• 1991

A quantization error model is suggested for analog to frequency(A/F) converter in strapdown inertial navigation system(SDINS),which is characterized by some white noise exciting the state variables. Also, effects on the performance of SDINS by analog to digital(A/D) converter and A/F converter are analyzed and compared via covariance simulation. As a result, A/F converter turns out to be superior to the A/D converter with respect to the induced navigation error and the difficulty in circuit realization. The quantization error model developed in this paper appears to be useful for optimal filter design.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.103-106
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• 2003

In this paper, we present a hybrid inertial and vision-based tracking system for VR applications. One of the most important aspects of VR (Virtual Reality) is providing a correspondence between the physical and virtual world. As a result, accurate and real-time tracking of an object's position and orientation is a prerequisite for many applications in the Virtual Environments. Pure vision-based tracking has low jitter and high accuracy but cannot guarantee real-time pose recovery under all circumstances. Pure inertial tracking has high update rates and full 6DOF recovery but lacks long-term stability due to sensor noise. In order to overcome the individual drawbacks and to build better tracking system, we introduce the fusion of vision-based and inertial tracking. Sensor fusion makes the proposal tracking system robust, fast, accurate, and low jitter and noise. Hybrid tracking is implemented with Kalman Filter that operates in a predictor-corrector manner. Combining bluetooth serial communication module gives the system a full mobility and makes the system affordable, lightweight energy-efficient. and practical. Full 6DOF recovery and the full mobility of proposal system enable the user to interact with mobile device like PDA and provide the user with natural interface.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1429-1432
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• 2005

This work is towards the development of a low-cost, small-sized inertial navigation system(INS) which consists of 3 accelerometers, 3 semiconductor gyros and a magnetic compass sensor. This paper explains in detail the structure of the developed system and proposes a 3 dimensional attitude estimation algorithm with Indirect Kalman Filter. The experiments are performed with the developed system attached to a 6 DOF robot for showing the effectiveness of the algorithm.