• International Journal of Aeronautical and Space Sciences
• /
• v.1 no.1
• /
• pp.70-80
• /
• 2000

The attitude knowledge error model is formulated for specifically KOMPSAT attitude determination system using the Lefferts/Markley/Shuster method, and the attitude determination(AD) error analysis is performed so as to investgate the on-board attitude determination capability of KOrea Multi-Purpose SATellite(KOMPSAT) using the covariance analysis method. Analysis results show there is almost no initial value effect on Attitude Determination (AD) error and the sensor noise effects on AD error are drastically decreased as is predicted because of the inherent characteristic of Kalman filter structure. However, it shows that the earth radiance effect of IR-sensor(earth sensor) and the bias effects of both IR-sensor and fine sun sensor are the dominant factors degrading AD error and gyro rate bias estimate error in AD system. Analysis results show that the attitude determination errors of roll, pitch and yaw axes are 0.056, 0.092 and 0.093 degrees, respectively. These numbers are smaller than the required values for the normal mission of KOMPSAT. Also, the selected on-orbit data of KOMPSAT is presented to demonstrate the designed AD system.

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

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1095-1098
• /
• 1996

In this work, attitude determination with Inertial Reference Unit as attitude sensor is considered. Usually, the attitude error from IRU increases because of gyro rate bias and noise. Therefore, other attitude sensors(sun sensor, horizon sensor, star tracker) are needed to compensate for error from IRU. In this paper, we use the extended Kalman filter for attitude estimation of spacecraft with IRU and star tracker.

• International Journal of Aeronautical and Space Sciences
• /
• v.14 no.1
• /
• pp.91-98
• /
• 2013

The rigorous requirements of modern spacecraft missions necessitate a precise attitude determination strategy. This paper mainly researches that, based on three space-borne attitude sensors: 3-axis rate gyros, 3-antenna GPS receiver and star-sensor. To obtain global attitude estimation after an information fusion process, a feedback-involved Federated Kalman Filter (FKF), consisting of two subsystem Kalman filters (Gyros/GPS and Gyros/Star-sensor), is established. In these filters, the state equation is implemented according to the spacecraft's kinematic attitude model, while the residual error models of GPS and star-sensor observed attitude are utilized, to establish two observation equations, respectively. Taking the sensors' different update rates into account, these two subsystem filters are conducted under a variable step size state prediction method. To improve the fault tolerant capacity of the attitude determination system, this paper designs malfunction warning factors, based on the principle of ${\chi}^2$ residual verification. Mathematical simulation indicates that the information fusion strategy overwhelms the disadvantages of each sensor, acquiring global attitude estimation with precision at a 2-arcsecs level. Although a subsystem encounters malfunction, FKF still reaches precise and stable accuracy. In this process, malfunction warning factors advice malfunctions correctly and effectively.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.6
• /
• pp.546-551
• /
• 2011

Tilt sensor is required to control the attitude of the biped robot when it walks on an uneven terrain. Vision sensor, which is used for recognizing human or detecting obstacles, can be used as a tilt angle sensor by comparing current image and reference image. However, vision sensor alone has a lot of technological limitations to control biped robot such as low sampling frequency and estimation time delay. In order to verify limitations of vision sensor, experimental setup of an inverted pendulum, which represents pitch motion of the walking or running robot, is used and it is proved that only vision sensor cannot control an inverted pendulum mainly because of the time delay. In this paper, to overcome limitations of vision sensor, Kalman filter for the multi-rate sensor fusion algorithm is applied with low-quality gyro sensor. It solves limitations of the vision sensor as well as eliminates drift of gyro sensor. Through the experiment of an inverted pendulum control, it is found that the tilt estimation performance of fusion sensor is greatly improved enough to control the attitude of an inverted pendulum.

• Journal of Power Electronics
• /
• v.9 no.4
• /
• pp.631-642
• /
• 2009

The sun is a useful reference direction because of its brightness relative to other astronomical objects and its relatively small apparent radius as viewed by spacecrafts near the Earth. Most satellites use solar power as a source of energy, and so need to make sure that solar panels are oriented correctly with respect to the sun. Also, some satellites have sensitive instruments that must not be exposed to direct sunlight. For all these reasons, sun sensors are important components in spacecraft attitude determination and control systems. To minimize components and structural mass, some components have multiple purposes. The solar cells will provide power and also be used as coarse sun sensors. A coarse Sun sensor is a low-cost attitude determination sensor suitable for a wide range of space missions. The sensor measures the sun angle in two orthogonal axes. The Sun sensor measures the sun angle in both azimuth and elevation. This paper presents the development of a model to determine the attitude of a small cube-shaped satellite in space relative to the sun's direction. This sensor helps small cube-shaped Pico satellites to perform accurate attitude determination without requiring additional hardware.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2006.10a
• /
• pp.85-86
• /
• 2006

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1966-1971
• /
• 2004

As the remote sensing satellite technology grows, the acquisition of accurate attitude and position information of the satellite has become more and more important. Due to the data processing limitation of the on-board orbit propagator and attitude determination algorithm, it is required to develop much more accurate orbit and attitude determination, which are so called POD (precision orbit determination) and PAD (precision attitude determination) techniques. The sensor and attitude dynamics simulation takes a great part in developing a PAD algorithm for two reasons: 1. when a PAD algorithm is developed before the launch, realistic sensor data are not available, and 2. reference attitude data are necessary for the performance verification of a PAD algorithm. A realistic attitude dynamics and sensor (IRU and star tracker) outputs simulation considering their physical characteristics are presented in this paper, which is planned to be used for a PAD algorithm development, test and performance verification.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.11 no.6
• /
• pp.30-37
• /
• 2008

The ARS(Attitude Reference System) calculates an attitude of a vehicle using inertial angular rate sensors and acceleration sensors. The attitude error of ARS increases due to the integration of angular rate sensor output. To reduce the attitude error an acceleration of sensor is used similar to leveling method of INS(Inertial Navigation System). When an acceleration of vehicle is increased, it is difficult to calculate the attitude error using acceleration sensor output. In this paper the estimation method of acceleration due to the attitude error only is proposed. Two methods of the attitude calculation depending on vehicle dynamics and the integration method of these two methods are proposed. To verify its performance the monte carlo simulation is performed and shows that it bounds attitude error of ARS to reasonable level.

• Journal of the Semiconductor & Display Technology
• /
• v.18 no.2
• /
• pp.87-91
• /
• 2019

In this paper, we have development of horizontal attitude monitoring system for agricultural robots. A two-axis gyro sensor and a two-axis accelerometer sensor are used to measure the horizontal attitude angle. The roll angle and pitch angle were measured through the fusion of the gyro sensor signal and the acceleration sensor signal for the horizontal attitude monitoring of the robot. This attitude monitoring system includes GPS and Bluetooth communication module for remote monitoring. The roll angle and pitch angle can be measured by the error of less than 1 degree and the linearity and the reproducibility of the output signal are excellent.