• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.524-532
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• 2002

This paper presents a new in-flight alignment method for an SDINS under large initial heading error. To handle large heading error, a new attitude error model is introduced. The attitude errors are divided into heading error and leveling errors using a newly defined horizontal frame. Some navigation error dynamic models are derived from the attitude error model for indirect feedback filtering of the in-flight alignment system. A Kalman filter with Position measurement is designed to estimate navigation errors as the indirect feedback filter Simulation results show that the proposed in-flight alignment method reduces the heading error very quickly from more than 40deg to about 5deg so as to apply a refined navigation filter. The total alignment process including leveling mode and navigation mode in addition to the proposed one allows large initial values not only in heading error but also in leveling errors.

• Proceedings of the Acoustical Society of Korea Conference
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• 1984.12a
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• pp.100-106
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• 1984

Traditional methods for estimating the location of underwater target, i.e. the triangulation method and the wavefront curvature method, have been utilized. The location of a target is defined by the range and the bearing, which estimates can be obtained by evaluating the time delay between neighboring sensors. Many components of error occur in estimating the target range, among which the error due to the fluctuation of heading angle is outstanding. In this paper, the wavefront curvature method was used. We considered the error due to the heading fluctuation as the $\beta$-density process, from which we analized the range estimates with $\beta$-density function exist in some finite limits, and its mean value and variation are depicted as a function of true range and heading fluctuation. Given heading angles and sensor separation, maximum estimated heading errors are presented as a function of true range.

• Journal of Navigation and Port Research
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• v.37 no.4
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• pp.329-335
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• 2013

This paper is to develop the position error equations including the attitude errors, the errors of nadir and ship's heading, and the errors of ship's position in the free-gyro positioning and directional system. In doing so, the determination of ship's position by two free gyro vectors was discussed and the algorithmic design of the free-gyro positioning and directional system was introduced briefly. Next, the errors of transformation matrices of the gyro and body frames, i.e. attitude errors, were examined and the attitude equations were also derived. The perturbations of the errors of the nadir angle including ship's heading were investigated in each stage from the sensor of rate of motion of the spin axis to the nadir angle obtained. Finally, the perturbation error equations of ship's position used the nadir angles were derived in the form of a linear error model and the concept of FDOP was also suggested by using covariance of position error.

• Journal of Positioning, Navigation, and Timing
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• v.2 no.2
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• pp.115-121
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• 2013

For the auto-landing operation of an air vehicle, the possibility of auto-landing operation should be first evaluated by testing the navigation performance through a flight test. In general, navigation performance is tested by analyzing north/east/down (NED) errors relative to reference equipment whose precision is about 8~10 times higher than that of a navigation system. However, to evaluate the auto-landing operation of an air vehicle, whether the air vehicle approaches a glide path aligned with the runway, within a specific error, needs to be examined rather than examining the north/east errors of the navigation system. Therefore, the longitudinal/lateral errors of air vehicle heading need to be analyzed. In this study, a method for analyzing the longitudinal/lateral errors of a navigation system was proposed as the navigation performance test method for evaluating the safety during the auto-landing of an air vehicle. Also, flight tests were performed six times, and the safety of auto-landing was examined by analyzing the performance using the proposed method.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.4
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• pp.29-35
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• 2008

In this paper, a new guidance law to reduce sensitivity to the initial heading errors is proposed. In order for shaping the input weights over the flight, we introduce the distribution functions expressed in terms of time-to-go and its inverse term. By applying the optimal control theory with the synthesized weights, the homing guidance law is derived. Also the characteristics of the proposed law are examined. Various computer simulations show the good performance of the proposed guidance.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.470-476
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• 2016

This paper proposes a practical algorithm for the reduction of measurement errors due to drift in a micro-electromechanical system (MEMS) gyros that are used for a mobile robot. Any drift in a MEMS gyro will cause an unbounded growth of errors in the estimation of heading, which makes it nearly useless in applications that require high accuracy over a long operating time. In proposed method, maneuvers of a cleaning robot are observed through encoders' measurement process and a decision to correct bias drift will be made if necessary. The method used in this paper is called the "heading estimation filter". To evaluate the accuracy of the proposed method, a comparison was made between the estimation of the heading of the cleaning robot and one from a motion capture system.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.1
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• pp.1-9
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• 2017

This paper proposes to improve the performance of a strap down inertial navigation system using a foot-mounted low-cost inertial measurement unit/magnetometer by configuring an attitude and heading reference system. To track position accurately and for attitude estimations, considering different dynamic constraints, magnetic measurement and a zero velocity update technique is used. A conventional strap down method based on integrating angular rate to determine attitude will inevitably induce long-term drift, while magnetometers are subject to short-term orientation errors. To eliminate this accumulative error, and thus, use the navigation system for a long-duration mission, a hybrid configuration by integrating a miniature micro electromechanical system (MEMS)-based attitude and heading detector with the conventional navigation system is proposed in this paper. The attitude and heading detector is composed of three-axis MEMS accelerometers and three-axis MEMS magnetometers. With an absolute algorithm based on gravity and Earth's magnetic field, rather than an integral algorithm, the attitude detector can obtain an absolute attitude and heading estimation without drift errors, so it can be used to adjust the attitude and orientation of the strap down system. Finally, we verify (by both formula analysis and from test results) that the accumulative errors are effectively eliminated via this hybrid scheme.

• 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 Advanced Research in Ocean Engineering
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• v.4 no.1
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• pp.16-24
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• 2018

This paper addresses the heading control of an offshore floating storage and regasification unit (FSRU) using a resolved motion and acceleration control (RMAC) algorithm. A turret moored vessel tends to have the slewing motion. This slewing motion may cause a considerable decrease in working time in loading and unloading operation because the sloshing in the LNG containment tank might happen and/or the collision between FSRU and LNGC may take place. In order to deal with the downtime problem due to this slewing motion, a heading control system for the turret moored FSRU is developed, and a series of model tests with azimuth thrusters on the FSRU is conducted. A Kalman filter is applied to estimate the low-frequency motion of the vessel. The RMAC algorithm is employed as a primary heading control method and modified I-controller is introduced to reduce the steady-state errors of the heading of the FSRU.

• Journal of Biosystems Engineering
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• v.33 no.6
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• pp.423-429
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• 2008

This study was performed to investigate the effects of inertial navigation system (INS) / global positioning system (GPS) sensor fusion for agricultural vehicle navigation. An extended Kalman filter algorithm was adopted for INS/GPS sensor fusion in an integrated mode, and the vehicle dynamic model was used instead of the navigation state error model. The INS/GPS system was consisted of a low-cost gyroscope, an odometer and a GPS receiver, and its performance was tested through computer simulations. When measurement noises of GPS receiver were 10, 1.0, 0.5, and 0.2 m ($1{\sigma}$), RMS position and heading errors of INS/GPS system at 5 m/s straight path were remarkably reduced with 10%, 35%, 40%, and 60% of those obtained from the GPS receiver, respectively. The decrease of position and heading errors by using INS/GPS rather than stand-alone GPS can provide more stable steering of agricultural equipments. Therefore, the low-cost INS/GPS system using the extended Kalman filter algorithm may enable the self-autonomous navigation to meet required performance like stable steering or more less position errors even in slow-speed operation.