• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.799-807
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• 2017

In this paper, a new method is proposed for estimating pedestrians' walking velocity based on lower-limb kinematics and wearable inertial measurement unit (IMU) sensors. While the soles and ground are not in contact during the walking cycle, the walking velocity can be estimated by integrating the acceleration output of the inertial sensor mounted on the pelvis. To minimize the effects of acceleration measurement errors caused by the tilt of the pelvis while walking, the estimated walking velocity based on lower-limb kinematics is imposed as the initial value in the acceleration signal integration process of the pelvis inertial sensor. In the experiment involving outdoor walking for six minutes, sensor drift due to error accumulation was not observed, and the RMS error in the walking velocity estimation was less than 0.08 m/s.

• Aerospace Engineering and Technology
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• v.3 no.1
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• pp.179-187
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• 2004

We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method which solves the problems of the Modified SPRT method. The problems of the Modified SPRT method to apply to inertial sensor system come from the effect of inertial sensor errors and the correlation of parity vector components. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which reduces the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled party vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.221-225
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• 1998

This paper is to present a method for recognizing an image of a tracking object by processing the image from a camera, whose attitude is controlled in inertial space with inertial co-ordinate system. In order to recognize an object, a pseudo-random M-array is attached on the object and it is observed by the camera which is controlled on inertial coordinate basis by inertial stabilization unit. When the attitude of the camera is changed, the observed image of M-array is transformed by use of affine transformation to the image in inertial coordinate system. Taking the cross-correlation function between the affine-transformed image and the original image, we can recognize the object. As parameters of the attitude of the camera, we used the azimuth angle of camera, which is de-fected by gyroscope of an inertial sensor, and elevation an91e of camera which is calculated from the gravitational acceleration detected by servo accelerometer.

• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.201-210
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• 1998

Inertial Navigation System(INS) can provide the vehicle position and velocity information using inertial sensor outputs without the use of external aids. Unfortunately INS navigation error increases with time due to inertial sensor errors, and therefore it is desirable to combine INS with external aids such as GPS, TACAN, OMEGA, and etc.. In this paper we propose an integration algorithm of commercial GPS/GLONASS and INS where an adaptive filter for signal processing of GPS/GLONASS receiver and the 12th order Kalman filter for aided strapdown INS(SDINS) we employed. Simulation results show that the proposed adaptive filter can effectively remove a randomly occurring abrupt jump due to sudden corruption of the received satellite signal and that the Kalman filter performs satisfactorily.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.314-320
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• 2012

This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.200-206
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• 2005

In this paper, a redundancy management system for aircraft is studied, and FDI (Fault Detection and Isolation) algorithm of inertial sensor system is proposed. UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional FDI method cannot isolate multiple faults in a triple redundancy system. In this paper, hardware based FDI technique is proposed, which combines a parity equation approach with the wavelet based technique, which is a model-free FDI method. To verify the effectiveness of the proposed FDI method, numerical simulations are performed.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1232-1237
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• 2008

This paper introduces an application of wavelet analysis to the sensor fusion of GPS/INS/baroaltimeter. Using wavelet analysis the baro-inertial altitude is decomposed into the low frequency content and the high frequency content. The high frequency components, 'details', represent the perturbed altitude change from the long time trend. GPS altitude is also broken down by a wavelet decomposition. The low frequency components, 'approximations', of the decomposed signal address the long-term trend of altitude. It is proposed that the final altitude be determined as the sum of both the details of the baro-inertial altitude and the approximations of GPS altitude. Then the final altitude exclude long-term baro-inertial errors and short-term GPS errors. Finally, it is shown from the test results that the proposed method produces continuous and sensitive altitude successfully.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.109-113
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• 2006

This paper presents an in-flight alignment method for strapdown inertial navigation systems based on the line-of-sight information. Unlike the existing methods, the proposed method utilizes only the 2-axis angle measurements of the onboard image sensor and does not require any explicit range measurements between the vehicle and landmarks. To improve the accuracy of all the position, velocity, and attitude estimates through the in-flight alignment, an error model of the image-sensor-aided SDINS is derived. A simulation study demonstrates that the accuracy of SDINS can be improved by the line-of-sight information only.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.1
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• pp.82-89
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• 2014

Recently, inertial sensors are popularly used for the location and position recognition of small devices for M2M/IoT. In this paper, we designed low power, low noise, small sized 6-axis inertial sensor IC for mobile applications, which uses a 3-axis piezo-electric gyroscope sensor and a 3-axis piezo-resistive accelerometer sensor. Proposed IC is composed of 3-axis gyroscope readout circuit, two gyroscope sensor driving circuits, 3-axis accelerometer readout circuit, 16bit sigma-delta ADC, digital filter and control circuit and memory. TSMC $0.18{\mu}m$ mixed signal CMOS process was used. Proposed IC reduces 27% of the current consumption of LSM330.

• Current Research on Agriculture and Life Sciences
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• v.32 no.2
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• pp.79-84
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• 2014

The precision aerial application of agricultural unmanned helicopters has become a new paradigm for small farms with orchards, paddy, and upland fields. The needs of agricultural applications require easy and affordable control systems. Recent developments of MEMS technology based on inertial sensors and high speed DSP have enabled the fabrication of low-cost attitude system. Therefore, this study evaluates inertial MEMS sensors for estimating the attitude of an agricultural unmanned helicopter. The accuracies and errors of gyro and acceleration sensors were verified using a pendulum system. The true motion values were calculated using a theoretical estimation and absolute encoder measurement of the pendulum, and then the sensor output was compared with reference values. When comparing the sensor measurements and true values, the errors were determined to be 4.32~5.72%, 3.53~6.74%, and 3.91~4.16% for the gyro rate and x-, z- accelerations, respectively. Thus, the measurement results confirmed that the inertial sensors are effective for establishing an attitude and heading reference system (AHRES). The sensors would be constructed in gimbals for the estimating and proving attitude measurements in the following paper.