• 한국군사과학기술학회지
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• 제9권1호
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• pp.5-12
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• 2006

This study describes an SDINS/GPS/ZUPT integration algorithm for land navigation systems. The SDINS error can be decoupled in two parts. The first part is the the Schuler component which does not depend on object motion parameters, and the other is the Non-Schuler part which depends on the product of object acceleration and azimuth error. Azimuth error causes SDINS error in proportion to the traversed distance. The proposed system consists of a GPS/SDINS integration system and an SDINS/ZUPT integration system, which are both realized by an indirect feedforward Kalman filter. The main difference between the two is whether the estimate includes the Non-Schuler error or not, which is decided by the measurement type. Consequently, subtracting GPS/SDINS outputs from SDINS/ZUPT outputs provide the Non-Schuler error information which can be applied to improving azimuth accuracy. Simulation results using the raw data obtained from a van test attest that the proposed SDINS/GPS/ZUPT system is capable of providing azimuth improvement.

• 한국항공우주학회지
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• 제42권3호
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• pp.221-228
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• 2014

본 논문은 유도형 활공 탄약의 운용 개념을 소개하고, 이를 위한 항법 알고리듬을 제안하였다. 유도형 활공 탄약은 기존의 유도형 탄약과는 다르게 사거리 증가를 위한 날개를 장착하고 활공하며, 이를 위해 날개 전개 전 탄체의 회전은 제거된다. 따라서 일정한 회전속도를 고려한 기존 유도형 탄약 항법 알고리듬은 활공 중에는 사용할 수 없다. 또한 탄체의 회전이 제거되면 회전 관성이 작아져 횡축이 불안정해져 횡축 가속도를 제어해야 하고, 이로 인해 롤 자세에 의한 횡축 중력 가속도 성분을 알 수 없다. 따라서 횡축 중력 가속도 성분을 기반으로 롤 자세를 추정하는 등속 수평 비행 상태를 가정한 기존 항법 알고리듬은 사용할 수 없다. 본 논문에서는 유도형 활공 탄약의 회전 중 상태 추정을 위해서는 Lucia가 제안한 알고리듬을 사용하였고, 활공 중 상태 추정을 위해서는 새로운 항법 알고리듬을 제안하였다.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.131-139
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• 2013

In recent years alternative navigation system such as a DBRN (Data-Base Referenced Navigation) system using geophysical information is getting attention in the military navigation systems in advanced countries. Specifically TRN (Terrain Referenced Navigation) algorithm research is important because TRN system is a practical DBRN application in South Korea at present time. This paper presents an integrated navigation algorithm that combines a linear profile-based TRN and INS (Inertial Navigation System). We propose a correlation analysis method between TRN performance and terrain roughness index. Then we propose a conditional position update scheme that utilizes the position output of the conventional linear profile type TRN depending on the terrain roughness index. Performance of the proposed algorithm is verified through Monte Carlo computer simulations using the actual terrain database. The results show that the TRN/INS integrated algorithm, even when the initial INS error is present, overcomes the shortcomings of linear profile-based TRN and improves navigation performance.

• 제어로봇시스템학회논문지
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• 제18권8호
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• pp.744-749
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• 2012

In this paper, we suggest that how to improve an accuracy of mobile robot's localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor's accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot's position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

• 제어로봇시스템학회논문지
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• 제7권1호
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• pp.1231-1239
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• 2001

This paper presents a new leveling algorithm that estimates the initial horizontal angles composed of roll angle and pitch angle for a moving or stationary vehicle. The system model of the EKF is designed by linearizing the nonlinear Euler angle differential equation. The measurement models are designed for the moving case and for the stationary case, respectively. The simulation results show that the leveling algorithm is ade-quate not only for acquiring the initial horizontal angles of the vehicle in the motion with acceleration and rotation but also for the stationary one.

• 제어로봇시스템학회논문지
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• 제6권2호
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• pp.138-145
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• 2000

In this paper an initial alignment algorithm for a strapdown inertial navigation system is implemented using a RISC CPU board. The algorithm computes roll pitch and yaw angles of the direction cosine matrix utilizing measured components of the specific force and earth rate when the navigation system is stationary. The coarse alignment algorithm is performed first and then the fine alignment algorithm containing a 3rd-order gyrocompass loop follows. The experimental set consists of an IMU a CPU board and a monitoring system Experimental results show that the implemented algorithm can be utilized in navigation systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.856-859
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• 1996

In this paper, a coarse alignment algorithm for strapdown inertial navigation system is proposed and evaluated analytically. The algorithm computes roll and pitch angles of the vehicle using accelerometer outputs, and then determines yaw angle with gyro outputs. It is referred, as two-step coarse alignment in this work. With the geometric relation between sensor outputs and roll, pitch and yaw angles, the algorithm error is analytically derived and compared with the previous coarse alignment algorithm introduced by Britting. The results show that the proposed two-step coarse alignment algorithm has better performance for pitch angle computation.

• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.183-189
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• 2011

An alignment algorithm for strapdown inertial navigation systems is proposed, in which the psi angle error model is utilized. The proposed alignment algorithm is derived from the Psi angle error model which has been widely used in real-time navigation systems. The equation for expecting steady state alignment error is also derived. The proposed algorithm was verified through real-time experiments. Experimental results show that the proposed algorithm can be used in the inertial navigation system and GNSS/INS integrated navigation system to get an initial attitude of the vehicle.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.774-778
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• 2008

The inaccuracy of inertial sensors used in low cost IMU's limits the usage to ARS, at best. Sensor fusion technologies are widely used to overcome this problem. GPS is the most popular secondary sensor, but GPS alone cannot fully compensate the IMU errors in the initial alignment process and rectilinear flights. This paper presents a new concept of aiding the low cost IMU with the sun line of sight vector. The simulation and experimental results in this paper proves that aiding of INS/GPS with the sun line of sight vector increases the observability and improves accuracy remarkably.

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.674-679
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• 1998

In this paper, a new coarse alignment algorithm is proposed for roughly determining the initial attitude of the vehicle. The algorithm, referred as two-step coarse alignment algorithm, computes roll and pitch angle of the vehicle using accelerometer outputs, and then determines yaw angle with gyro outputs. With the geometric relation between sensor outputs and attitude angles, the algorithm error is analytically derived and compared with the previous coarse alignment algorithm that computes a transformation matrix using accelerometer md gyro outputs simultaneously. The simulation is also performed by varying the sensor errors. The results show that the proposed two-step coarse alignment algorithm has better performance for east tilt angle.