• Journal of Positioning, Navigation, and Timing
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• v.8 no.3
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• pp.107-117
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• 2019

When a vehicle moves with a high rotation rate, it is not easy to measure the angular velocity using an off-the-shelf gyroscope. If the angular velocity is estimated using the extended Kalman filter in the gyro-free inertial navigation system, the effect of the accelerometer error and initial angular velocity error can be reduced. In this paper, in order to improve the navigation performance of the gyro-free inertial navigation system, an angular velocity estimation method is proposed based on an extended Kalman filter with an accelerometer random bias error model. In order to show the validity of the proposed estimation method, angular velocities and navigation outputs of a vehicle with 3 rev/s rotation rate are estimated. The results are compared with estimates by other methods such as the integration and an extended Kalman filter without an accelerometer random bias error model. The proposed method gives better estimation results than other methods.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1597-1609
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• 2015

This paper introduces the fundamentals of the conventional LC low-pass filter circuit in the fractional domain. First, we study the new fundamentals of fractional-order LC low-pass filter circuit including the pure real angular frequency, the pure imaginary angular frequency and the short circuit angular frequency. Moreover, sensitivity analysis of the impedance characteristics and phase characteristics of the LC low-pass filter circuit with respect to the system variables is studied in detail, which shows the greater flexibility of the fractional-order filter circuit in designs. Furthermore, from the filtering property perspective, we systematically investigate the effects of the system variables (LC, frequency f and fractional orders) on the amplitude-frequency characteristics and phase-frequency characteristics. In addition, the detailed analyses of the cut-off frequency and filter factor are presented. Numerical experimental results are presented to verify the theoretical results introduced in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.103-107
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• 2006

At present, most efforts tend to develop a INS which is only based linear accelerometers, because of the low cost micro-machining gyroscopes lack of the accuracy needed for precise navigation application and possible achieving the required levels of precise for micro-machining accelerometer. Although it was known in theory that a minimum of six accelerometers are required for a complete description of a rigid body motion, and any configuration of six accelerometers (except for a "measure zero " set of six-accelerometer schemes) will work. Studies on the feasible configuration of GF-INS indicate that the errors of angular velocity resolved from the six accelerometers scheme are diverged with time or have multi solutions. The angular velocity errors are induced by the biases together with the position vectors of the accelerometers, therefore, in order to treat with the problem just mentioned, researchers have been doing many efforts, such as the extra three accelerometers or the magnetometers may be taken as the reference information, the extended Kalman filter (EKF) involved to make the angular velocity errors bound and be estimated, and so on. In this paper, the typical configurations of GF-INS are introduced; for each type GF-INS described, the solutions to the angular velocity and the specific force are derived and the characteristic is indicated; one of the corresponding extend Kalman filters are introduced to estimate the angular errors; parts of the simulation results are presented to verify the validity of the equations of angular velocity and specific force and the performance of extend Kalman filter.

• ETRI Journal
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• v.38 no.2
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• pp.356-365
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• 2016

This research proposes a modified particle filter to increase the accuracy of vehicle tracking in a noisy and occluded medium. In our proposed method for vehicle tracking, the direction angle of a target vehicle is calculated. The angular difference between the motion direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted depending on their angular distance to the motion direction. Those particles moving in a direction similar to that of the target vehicle are assigned larger weights; this, in turn, increases their probability in a given likelihood function (part of the process of estimation of a target's state parameters). The proposed method is compared against a condensation algorithm. Our results show that the proposed method improves the stability of a particle filter tracker and decreases the particle consumption.

• Korean Journal of Optics and Photonics
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• v.2 no.2
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• pp.83-88
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• 1991

Studies on space-invariant pattern recognition have been carried out from various approaches. Pattern recognition system using SDF filter, from weighted linear summation of tranining images, has been the focus of research since its first appearence. In this thesis, off-axis pSDF spatial matched filter has been constructed by combining angular multiplexing of off-axis reference plane wave with pSDF filter made from pseudo-inverse algorithm, and transformed to phase only filter. From observation of the correlation responses in the correlation plane, it is shown that proposed off-axis pSDF spatial matched filter is available to pattern classification and can be used for optical correlator.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.10
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• pp.853-861
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• 2016

This paper deals with a new technique utilizing the angular speed of the reaction wheels to determine attitudes and angular rates for gyroless satellites. The suggested algorithm in this study is designed to determine the precise attitude and angular rates under actual space environments by the support of the angular speeds of reaction wheels based on the extended Kalman filter. Furthermore, the proposed approach is also designed to estimate not only the attitude and angular rates of spacecraft but the external disturbances. The numerical simulation was conducted for gyloless spacecraft installed with four reaction wheels of the pyramid-type configuration. The performance of the proposed algorithm is verified by using numerical simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2526-2531
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• 2005

A practical pinch torque estimator based on the Kalman filter is proposed for low-cost anti-pinch window control systems. To obtain the accurate angular velocity from Hall-effect sensor measurements, the angular velocity calculation algorithm is executed with additional procedures for removing the measurement noises. Apart from the previous works using the angular velocity estimates and torque estimates for detecting the pinched condition, the torque rate is augmented to the system model and the proposed pinch estimator is derived by applying the steady-state Kalman filter recursion to the model. The motivation of this approach comes from the idea that the bias errors in torque estimates due to the motor parameter uncertainties can be almost eliminated by introducing the torque rate state. For detecting the pinched condition, a systematic way to determine the threshold level of the torque rate estimates is also suggested via the deterministic estimation error analysis. Simulation results are given to certify the pinch detection performance of the proposed algorithm and its robustness against the motor parameter uncertainties.

• Journal of Ocean Engineering and Technology
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• v.31 no.2
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• pp.164-169
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• 2017

Studies were performed on an ARS using SDINS's RLG and the geomatic sensor. To develop the ARS, experiments were performed to determine the characteristics of the RLG and geomatic sensor. Based on the results, to reduce the angular position errors of the RLG, which accumulate from the angular velocity data, an algorithm was studied that uses the Extended Kalman filter (EKF) to compensate the RLG data and geomatic sensor data. To verify the performance of the developed algorithm for reducing the cumulative angular errors, experiments that included the developed EKF were performed. Through these, it was shown that a drastic reduction in the angular errors of the RLG were achieved.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.871-877
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• 2018

In this paper, we propose a triple nested PID control scheme for stable hovering of a quadrotor and propose a complementary filter based sensor fusion technique to improve the performance of attitude, altitude and velocity measurement. The triple nested controller has a structure in which a double nested attitude controller that has the angular velocity PD controller in inner loop and the angular PI controller in outer loop, is nested in a velocity control loop to enable stable hovering even in the case of disturbance. We also propose a sensor fusion technique by applying a complementary filter in order to reduce the noise and drift error included in the acceleration and gyro sensor and to measure the velocity by fusing image, gyro, and acceleration sensor. In order to verity the performance, we applied the proposed control and measurement scheme to hovering control of quadrotor.