• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.91-91
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• 2000

In this paper, the error compensation method of the attitude reference system with low-cost IMU is proposed. In general, the attitude error calculated by gyro grows with time. Therefore the additional information is required to compensate the drift. The attitude angles can be bound by accelerometer mixing algorithm and the heading angle can be aided by GPS velocity information. The Kalman filter is used for error compensation. The result is verified by comparing with the attitude calculated by medium-grade IMU, LP-81.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.10
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• pp.1092-1099
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• 1992

In this paper, a sensitivity of the gravity acceleration $(0{\sim}1G)$ for a fiber-optic accelerometer is demonstrated. A single mode optical fiber Mach-Zehnder interferometer was used to detect the change in optical path length produced by the strain in the fiber from probe mass about 1 gram. The phase conversion gain of the piezoelectric cylinder in the reference arm with this system measures 0.88rad./v.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.1
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• pp.87-93
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• 2017

This paper investigates active noise control of tower-type air conditioners using the filtered-x least mean square (FXLMS) algorithm to reduce fan blower noise transmission. Firstly, the main components required for the active control system including the error sensor, the control speaker and the reference sensors are selected. Since the noise could significantly reduce if the reference signal includes every frequency response information, a various reference signals from accelerometers and a microphone are used. Secondly, the controller based on the FXLMS algorithm with a single-channel reference signal is implemented. Then, the control performance is examined experimentally for the different reference signals. It is found that the accelerometer signal well possesses the motor vibration related noise and a microphone signal could includes global noise. When using the reference signal with a microphone located near the motor and the fan blower, the active control system reduces the noise globally, except for several peaks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2511-2520
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• 2011

This paper describes the parameter adjustment method of fuzzy membership function to improve the performance of multi-sensor fusion system using adaptive fuzzy-Kalman filter and cross-validation. The adaptive fuzzy-Kanlman filter has two input parameters, variation of accelerometer measurements and residual error of Kalman filter. The filter estimates system noise R and measurement noise Q, then changes the Kalman gain. To evaluate proposed adaptive fuzzy-Kalman filter, we make the two-axis AHRS(Attitude Heading Reference System) using fusion of an accelerometer and a gyro sensor. Then we verified its performance by comparing to NAV420CA-100 to be used in various fields of airborne, marine and land applications.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.3
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• pp.555-564
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• 2017

In this paper, a new technique for attitude and heading reference system (AHRS) using low-cost MEMS sensors of the gyroscope, accelerometer, and magnetometer is addressed particularly in vibration environments. The motion of MEMS sensors interact with the scale factor and cross-coupling errors to produce random errors by the harsh environment. A new adaptive attitude estimation algorithm based on the Kalman filter is developed to overcome these undesirable side effects by analyzing windowed measurement error covariance. The key idea is that performance degradation of accelerometers, for example, due to linear vibrations can be reduced by the proposed measurement error covariance analysis. The computed error covariance is utilized to the measurement covariance of Kalman filters adaptively. Finally, the proposed approach is verified by using numerical simulations and experiments in an acceleration phase and/or vibrating environments.

• Korean Journal of Applied Biomechanics
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• v.19 no.1
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• pp.159-166
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• 2009

The purpose of this study was to develop and automatic gait event detection algorithm using single accelerometer which is attached at the top of the shoe. The sinal vector magnitude and anterior-posterior(x-axis) directional component of accelerometer were used to detect heel strike(HS) and toe off(TO), respectively. To evaluate proposed algorithm, gait event timing was compared with that by force plate and kinematic data. In experiment, 7 subjects performed 10 trials level walking with 3 different walking conditions such as fast, preferred & slow walking. An accelerometer, force plate and 3D motion capture system were used during experiment. Gait event by force plate was used as reference timing. Results showed that gait event by accelerometer is similar to that by force plate. The distribution of differences were spread about $22.33{\pm}17.45m$ for HS and $26.82{\pm}14.78m$ for To and most error was existed consistently prior to 20ms. The difference between gait event by kinematic data and developed algorithm was small. Thus it can be concluded that developed algorithm can be used during outdoor walking experiment. Further study is necessary to extract gait spatial variables by removing gravity factor.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.59-64
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• 2004

In this paper, the error compensation method of the low-cost IMU is proposed. In general, the position and attitude error calculated by accelerometers and gyros grows with time. Therefore the additional information is required to compensate the drift. The attitude angles can be bound accelerometer mixing algorithm and the heading angle can be aided by single antenna GPS velocity. The Kalman filter is used for error compensation. The result is verified by comparing with the attitude calculated by Attitude Heading Reference System with Micro Electro Mechanical System for a basis

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

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.66-73
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• 2016

An Inertial Measurement Unit (IMU)-based Attitude and Heading Reference System (AHRS) can calculate attitude and heading information with long-term accuracy and stability by combining gyro, accelerometer, and magnetic compass signals. Motivated by this characteristic of the AHRS, this paper presents a Motion-Tracking and Localization (MTL) method for a person or walking robot using multi-AHRSs. Five AHRSs are attached to the two calves, two thighs, and waist of a person/walking robot. Joints, links, and coordinate frames are defined on the body. The outputs of the AHRSs are integrated with link data. In addition, a supporting foot is distinguished from a moving foot. With this information, the locations of the joints on the local coordinate frame are calculated. The experimental results show that the presented MTL method can track the motion of and localize a person/walking robot with long-term accuracy in an infra-less environment.

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