• Journal of the Semiconductor & Display Technology
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• v.9 no.2
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• pp.41-47
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• 2010

In this paper we suggest an improvement upon the previous method of estimating a body's attitude. This paper presents a method that overcomes the shortcomings of previous studies. Applying the method of separating the acceleration of gravity component from the accelerometer's output improves the performance of the attitude estimation and extends the scope. In order to apply the method of the attitude estimation in an actively moving body, a new acceleration value containing the acceleration of gravity is calculated. This paper also proposes the method which minimizes the estimation error in estimating the moving body's attitude which is changing rapidly. Finally, this paper suggests a method that detects the gyroscope's drift and compensates for this drift using accelerometer. Applying the method improves the performance of the attitude estimation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.876-881
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• 2003

Reliable attitude estimation during the launch and early orbit phase is a critical issue for a satellite. Typically gyroscopes and other sensors are utilized to estimate the attitude during this phase. It is difficult to estimate the attitude quickly and reliably using gyroscopes because it requires a large computational load and accurate sensor measurements. Furthermore, the gyroscope failure may lead to the loss of the satellite. This paper suggests a simple attitude estimation method of a low earth orbit satellite without using gyroscopes, but only using sun sensors and magnetometers in the sun-acquisition mode. Using Kompsat-I telemetry data, we verified that the suggested algorithm provides attitude estimation within 3 degrees on each axis.

• Advances in aircraft and spacecraft science
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• v.4 no.3
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• pp.335-351
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• 2017

Kalman filter based spacecraft attitude estimation has been used in many space missions and has been widely discussed in literature. While some models in spacecraft attitude estimation include spacecraft dynamics, most do not. To our best knowledge, there is no comparison on which model is a better choice. In this paper, we discuss the reasons why spacecraft dynamics should be considered in the Kalman filter based spacecraft attitude estimation problem. We also propose a reduced quaternion spacecraft dynamics model which admits additive noise. Geometry of the reduced quaternion model and the additive noise are discussed. This treatment is easier in computation than the one with full quaternion. Simulations are conducted to verify our claims.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.621-626
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• 2005

With precise GPS carrier positioning result, we can get attitude information if GPS antenna has adequate attaching position on the vehicle. In this case, baseline length information can be bandied as an additional measurement or constraint. In this paper, we have proposed a method to improve the attitude accuracy. To overcome nonlinearity of baseline observation model, we analyze attitude estimation result using existing estimation method like a least square method and Kalman filter, and apply a new nonlinear estimation method an unscented Kalman filter Finally we confirm the improvement of attitude estimation result in the case of appling the unscented Kalman filter.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.616-619
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• 2003

In this paper, we develop an input device equipped with accelerometers and gyroscopes. The installed sensors measure the inertial measurements i.e., accelerations and angular rates produced by the movement of the system when a user is writing on the plane surface or in the three dimensional space. The gyroscope measurement are integrated once to give the attitude of the system and consequently used to remove the gravity included in the acceleration measurements. The compensated accelerations bin doubly integrated to yield the position of the system. Due to the integration processes involved in recovering the users'motions, the accuracy of the position estimation significantly deteriorates with time. Among various error sources of the system incorrect estimation of attitude causes the largest portion of the positioning error since the gravity is not fully cancelled. In order to solve this problem, we propose a Kalman filler-based attitude estimation algorithm which fuses measurement data from accelerometers and gyroscopes by fuzzy logic approach. In addition, the online calibration of the gyroscope biases are performed in parallel with the attitude estimation to give more accurate attitude estimation. The effectiveness and the feasibility of the presented system is demonstrated through computer simulations and actual experiments.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.31-46
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• 2009

An Unscented Kalman Filter (UKF) for estimation of the attitude and rate of a spacecraft using only magnetometer vector measurement is developed. The attitude dynamics used in the estimation is the nonlinear Euler's rotational equation which is augmented with the quaternion kinematics to construct a process model. The filter is designed for small satellite in low Earth orbit, so the disturbance torques include gravity-gradient torque, magnetic disturbance torque, and aerodynamic drag torque. The magnetometer measurements are simulated based on time-varying position of the spacecraft. The filter has been tested not only in the standby mode but also in the detumbling mode. Two types of actuators have been modeled and applied in the simulation. The PD controller is used for the two types of actuators (reaction wheels and thrusters) to detumble the spacecraft. The estimation error converged to within 5 deg for attitude and 0.1 deg/s for rate respectively when the two types of actuators were used. A joint state parameter estimation has been tested and the effect of the process noise covariance on the parameter estimation has been indicated. Also, Monte-Carlo simulations have been performed to test the capability of the filter to converge with the initial conditions sampled from a uniform distribution. Finally, the UKF performance has been compared to that of the EKF and it demonstrates that UKF slightly outperforms EKF. The developed algorithm can be applied to any type of small satellites that are actuated by magnetic torquers, reaction wheels or thrusters with a capability of magnetometer vector measurements for attitude and rate estimation.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.41-43
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• 2004

This paper is concerned with attitude estimation using low cost, small-sized accelerometers and gyroscopes. A two step extended Kalman filter is proposed, which adaptively compensates external acceleration. External acceleration is the main source of estimation error. In the proposed filter, direction of external acceleration is estimated. According to the estimated direction, the accelerometer measurement covariance matrix of the two step extended Kalman filter is adjusted. The proposed algorithm is verified through experiments.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.61-68
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• 2005

This paper is concerned with attitude control of 2 rotor 1 DOF aerial vehicle. The proposed controller consists of two parts: the attitude estimation filter part and PID controller part. For attitude estimation, performance of 3 different filters (complementary filters, Kalman filter, indirect Kalman filters) are tested and compared. For the PID controller, characteristic ratio assignment methods are used to assign PID coefficients. Through experiments, it is shown that attitude of the vehicle successfully follows the step command.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.216-224
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• 2014

This paper compares methods for attitude estimation of a UUV(Unmanned Underwater Vehicle). Attitude estimation plays a key role in underwater navigation using DVL(Doppler Velocity Log). The paper proposes attitude estimation methods using EKF(Extended Kalman Filter), UKF(Unscented Kalman Filter), and CF(Complementary Filter). It derives methods using the measurements from MEMS-AHRS(Microelectromechanical Systems-Attitude Heading Reference System) and DVL. The methods are used for navigation in a test pool and their navigation performance is compared. The results suggest that even if there is no measurement relative to some absolute landmarks, DVL-only navigation can be useful for navigation in a limited time and range.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.453-458
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• 2015

We presented a quad-rotor controlling algorithm design by using sensor fusion in this paper. The controller design technique was performed by a PD controller with a Kalman filter and compensation algorithm for increasing the stability and reliability of the quad-rotor attitude. In this paper, we propose an attitude estimation algorithm for quad-rotor based sensor fusion by using the Kalman filter. For this reason, firstly, we studied the platform configuration and principle of the quad-rotor. Secondly, the bias errors of a gyro sensor, acceleration and geomagnetic sensor are compensated. The measured values of each sensor are then fused via a Kalman filter. Finally, the performance of the proposed algorithm is evaluated through experimental data of attitude estimation. As a result, the proposed sensor fusion algorithm showed superior attitude estimation performance, and also proved that robust attitude estimation is possible even in disturbance.