• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.522-526
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• 2015

Generally, underwater unmanned vehicle have adopted an inertial navigation system (INS), dead reckoning (DR), acoustic navigation and geophysical navigation techniques as the navigation method because GPS does not work in deep underwater environment. Even if the tactical inertial sensor can provide very detail measurement during long operation time, it is not suitable to use the tactical inertial sensor for small size and low cost UUV because the tactical inertial sensor is expensive and large. One alternative to INS is attitude heading reference system (AHRS) with the micro-machined electro mechanical system (MEMS) inertial sensor because of MEMS inertial sensor's small size and low power requirement. A cost effective and small size attitude heading reference system (AHRS) which incorporates measurements from 3-axis micro-machined electro mechanical system (MEMS) gyroscopes, accelerometers, and 3-axis magnetometers has been developed to provide a complete attitude solution for UUV. The AHRS based MEMS overcome many problems that have inhibited the adoption of inertial system for small UUV such as cost, size and power consumption. Several evaluation experiments were carried out for the validation of the developed AHRS's function and these experiments results are presented. Experiments results prove the fact that the developed MEMS AHRS satisfied the required specification.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.4
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• pp.308-315
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• 2016

A new technique for Attitude & Heading Reference System (AHRS) by using sequential measurement noise covariance (SMNC) is addressed in a vibration environments in this paper. In particular, a low-cost inertial measurement unit in general diverges in the acceleration phase or vibrating environments due to inherent properties of gravity and acceleration. In this paper, by considering current and prior measurements to estimate actual attitudes and headings in a local frame, the proposed technique overcomes these problems efficiently. Finally, the performance of the suggested approach is verified by numerical simulations.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2077-2078
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• 2006

This paper describes the development or a closed-loop Strapdown Attitude Reference System (SARS) algorithm integrated filtering estimator for determining attitude reference for railway and aviation system using fuzzy inference. The SARS consists of 3 single-axis rate gyms in conjunction with 2 single-axis accelerometers. For optimal values of fuzzy systems, we utilize on-line scheduling method for initial values and then use genetic algorithms for fine tuning. Implementation using experimental test data of unmanned aerial vehicle has been performed in order to verify the estimation. The proposed fuzzy inference based SARS demonstrate that more accurate performance can be achieved in comparison with conventional one. The estimation results were compared with the on-board vertical gyro as the reference standard.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.852-860
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• 2003

We introduce the error models for an attitude determination system(ADS) with gyroscopes and stellar sensor. The ADS error models are derived according to the definition of the reference frame and of the attitude error. The equivalent error models applicable to the attitude determination system with large attitude errors are presented. The simulation results show that the proposed error models improve performance of the attitude determination system.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2399-2410
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• 2017

In this paper, a linear matrix inequality-based sampled-data fuzzy observer design method is proposed based on the exact discretization approach. In the proposed design technique, a numerically relaxed observer design condition is obtained by using the discrete-time fuzzy Lyapunov function. Unlike the existing studies, the designed observer is robust to the uncertain premise variable because the fuzzy observer is designed under the imperfect premise matching condition, in which the membership functions of the system and observer are mismatched. In addition, we apply the proposed method to the state estimation problem of the attitude and heading reference system (AHRS). To do this, we derive a Takagi-Sugeno fuzzy model for the AHRS system, and validate the proposed method through the hardware experiment.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.222-231
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• 2016

This paper proposes a new method achieving computationally efficient attitude reference system for low cost strapdown sensors and microprocessor platform. The main idea in this method is to define and compare velocity differential vectors, geometrically computed from INS and GPS data with different update rate, for generating attitude error measurements which is further used for filter construction. A quaternion based Kalman filter configuration is applied for the attitude estimation with the adapted measurement model of differential vector comparison. Linearized model for Extended Kalman Filter and low pass filtered characteristics of measurement greatly extend the affordability of the proposed algorithm to the field of simple low cost embedded systems. For performance verification, experiment are done employing a practical low cost MEMS IMU and GPS receiver specification. Performance comparison with a high grade navigation system demonstrated good estimation result.

• 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.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.2
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• pp.167-177
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• 2002

In Strapdown Inertial Navigation System(SDINS), error models based on previously proposed conversion equations between the attitude errors, are only valid in case the attitude errors are small. The SDINS error models have been independently studied according to the definition of the reference frame and of the attitude error. The conversion equations between the attitude errors applicable to SDINS with large attitude errors are newly derived. Lyapunov transformation matrices are also derived from the obtained results. Furthermore the general method, which is independent of the attitude error and the reference frame to derive SDINS error model, is proposed using the Lyapunov transformation.