• IEMEK Journal of Embedded Systems and Applications
• /
• v.9 no.5
• /
• pp.277-283
• /
• 2014

In this paper, we propose a control system for synchronizing attitude between an Android smartphone and a mobile robot. The control system is comprised of a smartphone and a mobile robot. The smartphone transports its attitude to the mobile robot and receives the attitude of mobile robot through bluetooth communication. Further, the smartphone displays the mobile robot on the screen by using embedded camera, which can be used as a pseudo augmented reality. Comparing the received attitude data from smartphone, the mobile robot measures its attitude by an AHRS(attitude heading reference system) and controls its attitude. Experiments show that the synchronization performance of the proposed system is maintained in the error range of $1^{\circ}$.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.39 no.2
• /
• pp.128-136
• /
• 2011

An approach to improve the performance of SDINS and GPS integrated system for bank-to-turn flight vehicles is described. Then, it is shown through the simulation that a specific gyro misalignment error results in an increased heading error of SDINS. A new modelling method is presented herein for identifying of sensor and attitude error. The main advantage of the proposed method is that it not only estimates the gyro misalignment error of SDINS, but also improves estimate performance of heading error of SDINS in the presence of the gyro misalignments.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.38 no.4
• /
• pp.342-351
• /
• 2010

UAV (Unmanned Aerial Vehicle) have an INS(Inertial Navigation System) equipment and also have an electro-optical Equipment for mission. This paper proposes the vision based attitude estimation algorithm using Kalman Filter and Optical flow for UAV. Optical flow is acquired from the movie of camera which is equipped on UAV and UAV's attitude is measured from optical flow. In this paper, Kalman Filter has been used for the settlement of the low reliability and estimation of UAV's attitude. Algorithm verification was performed through experiments. The experiment has been used rate table and real flight video. Then, this paper shows the verification result of UAV's attitude estimation algorithm. When the rate table was tested, the error was in 2 degree and the tendency was similar with AHRS measurement states. However, on the experiment of real flight movie, maximum yaw error was 21 degree and Maximum pitch error was 7.8 degree.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.10 no.2
• /
• pp.160-169
• /
• 2007

In this paper, we have described and simulated the effect analysis and correction of phase errors in the SAR rawdata induced by satellite attitude errors such as drift, jitter. This simulation is based on the FSA(Frequency Scaling Algorithm) for high resolution image formation of the Spotlight SAR. Phase errors produce the degradation of SAR image quality such as loss of resolution, geometric distortion, loss of contrast, spurious targets, and decrease in SNR. To resolve this problem, this paper presents method for correction of phase errors using the PGA(Phase Gradient Algorithm) in connection with the FSA. Several results of the phase errors correction are presented for Spotlight SAR rawdata.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.9
• /
• pp.881-885
• /
• 2008

To calculate the attitude in ARS(Attitude Reference System) using 3 gyros and 3 accelerometers, gyro drift must be compensated with accelerometer to avoid divergence of attitude error. Kalman filter is most popular method to integrate those two sensor outputs. In this paper, new Kalman filtering method is proposed for roll and pitch attitude estimation. New states are defined to make linear equation and algorithm for changing Kalman filter parameters is proposed to ignore disturbances of acceleration. This algorithm can be easily applied to low cost ARS.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.45 no.2
• /
• pp.265-272
• /
• 1996

In this paper, attitude computation algorithm for a strap down ARS(Attitude Reference System)of an underwater vehicle has been studied. Attitude errors o the ARS using low-level gyroscopes tend to increase with time due to gyroscope errors. To cope with this problem, a mixing algorithm of accelerometer aided attitude computation has been developed. The algorithm can successfully bound the error increase for cruising motion, but it gives instantaneously large errors when a vehicle maneuvers. To improve the performance in case of vehicle's maneuver, a new attitude computation mixing algorithm complying state of vehicle and to manage the adjustment of the gains which are invariant in the existing algorithm. In addition, a gain scheduling method is applied to fuzzy inference composition process for real-time computation. Monte Carlo simulation results show that the proposed algorithm provides better performance than the existing algorithm.

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

• Journal of Magnetics
• /
• v.22 no.2
• /
• pp.315-325
• /
• 2017

Magnetically suspended sensitive gyroscopes (MSSGs) provide an interesting alternative for achieving precious attitude angular measurement. To effectively reduce the measurement error caused by the non-uniformity of the air-gap flux density in a MSSG, this paper proposes a novel compensation method based on measuring and modeling of the air-gap flux density. The angular velocity measurement principle and the structure of the MSSG are described, and then the characteristic of the air-gap flux density has been analyzed in detail. Next, to compensate the flux density distribution error and improve the measurement accuracy of the MSSG, a real-time compensation method based on the online measurement with hall probes is designed. The common issues caused by the non-uniformity of the air-gap flux density can be effectively resolved by the proposed method in high-precision magnetically suspended configurations. Comparative simulation results before and after compensation have verified the effectiveness and superiority of the proposed compensation method.

• Aerospace Engineering and Technology
• /
• v.1 no.2
• /
• pp.141-148
• /
• 2002

The purpose of this study is to enhance geo-location accuracy of the image data acquired by the Electro-Optical Camera(EOC) onboard KOMPSAT-1. EOC image data were analyzed to verify geo-location error. It was found that the major contribution was the time mark inaccuracy and attitude knowledge error. This study shows that the geo-location accuracy can be enhanced by modifying the time and attitude data of the ancillary data.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.64.2-64
• /
• 2001

In this paper, fabricated is a motion capture and attitude detection system for Head Mounted Display HMD composed of three low-price and low-grade micro gyroscopes and a micro-controller, To calculate attitude of a body, modified INS algorithm is used. Because the micro gyroscope has much bias drift error, scale factor error, and run-to-run bias error, the motion of a body can not be measured exactly if the general INS algorithm and micro gyroscopes are used. To reduce the errors, three accelerometers can be used. In this case, however, the size and power consumption become too large to use in HMD system. The modified INS algorithm use the grid map and the characteristics of the human motions.