• Journal of information and communication convergence engineering
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• 제17권3호
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• pp.205-212
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• 2019

Motion tracking and localization devices are an important building block of motion tracking systems in a virtual reality (VR) environment. This study is about improving the accuracy of motion and location for enhancing user immersion in experience type VR environment to position tracking technique. In this study, we propose and test a design of such a device. The module data test of the attitude and heading reference system shows that the implementation with the MPU-9250 sensor is successful and adequate to be used with short operation time. We consider various sensor hardware dependencies of VR, and compare various correction methods and filtering methods to lower the motion to photon (MTP) time that user movement is fully reflected on the display using sensor devices. The Kalman filter is used to combine the accelerometer with the gyroscope in the sensing unit.

• 소음진동
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• 제10권5호
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• pp.886-891
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• 2000

In this paper, an iterative array shape estimation technique is presented, which is based on the use of the least squares polynomial fitting to the data from heading sensors. The estimated polynomial shape model is then used for calculating the hydrophone positions on the assumption that the arc distances between sensors are constant. In order to verify the applicability of the proposed algorithm, numerical simulations are performed using two types of non-linear array shapes. In addition the noise effects of heading sensors on the array shape estimation results and the performance of beamformer are also investigated.

• Journal of Biosystems Engineering
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• 제33권6호
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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.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1675-1682
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• 2017

This paper deals with three dimensional orientation estimation algorithm for an attitude and heading reference system (AHRS) based on nine-axis inertial/magnetic sensor signals. In terms of the orientation estimation based on the use of a Kalman filter (KF), the quaternion is arguably the most popular orientation representation. However, one critical drawback in the quaternion representation is that undesirable magnetic disturbances affect not only yaw estimation but also roll and pitch estimations. In this paper, a sequential direction cosine matrix-based orientation KF for AHRS has been presented. The proposed algorithm uses two linear KFs, consisting of an attitude KF followed by a heading KF. In the latter, the direction of the local magnetic field vector is projected onto the heading axis of the inertial frame by considering the dip angle, which can be determined after the attitude KF. Owing to the sequential KF structure, the effects of even extreme magnetic disturbances are limited to the roll and pitch estimations, without any additional decoupling process. This overcomes an inherent issue in quaternion-based estimation algorithms. Validation test results show that the proposed method outperforms other comparison methods in terms of the yaw estimation accuracy during perturbations and in terms of the recovery speed.

• 센서학회지
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• 제26권4호
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• pp.286-291
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• 2017

With regards to heading estimation using gyroscope and magnetometer signals, magnetic disturbance added in the magnetometer signals is a main degradation factor in the estimation accuracy. Although there are a number of existing mechanisms that may properly compensate for the magnetic disturbances, they are designed to react only to the magnetic disturbances, but not to the time derivative of disturbances. Note that the sensors may experience abrupt changes in the magnetic disturbances, particularly for ambulatory applications. This paper proposes a magnetic disturbance model-embedded heading estimation filter for time-varying magnetic environments. The proposed magnetic disturbance model is based on a first-order Markov chain with a conditional switching technique depending on the time derivative of disturbances. Once a high amount of derivative is detected, the corrupted magnetometer signals are discarded to protect the filter from them. In our experimental results, the averaged heading error of tests was $1.46^{\circ}$, while that of the original approach without switching was $5.75^{\circ}$.

• 수산해양기술연구
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• 제30권3호
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• pp.182-188
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• 1994

In recent years, navigational and fisheries instruments are rapidly advancing. Especially data processing. data transferring and data interchange throughout the digital signals has been in high progress. Even though the ship's heading is also provided by a gyro-compass, an electro-magnetic compass studying by us currently is easy to issue adequate data to instruments requiring the information for the ship's heading. especially in small fishing boats. As the main element of the electro-magnetic compass is a three-axis magnetic sensors, the developing of the high performance sensor is in highly necessity in the beginning. This paper describes on the development of electro-magnetic compass of three-axis fixed type by using three-axis detection new type magnetic sensor without gimbals. even though usual electro-magnetic compass have to need necessarily a gimbal system in order to keep horizontal condition of the compass.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.94.5-94
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• 2001

Unrestricted measurement method of three-dimensional walking distance utilizing body acceleration and terrestrial magnetism is discussed. The three-dimensional walking distance is derived by the integration of the three dimensional acceleration of foot during swing phase. Since the sensor system attached on the foot rotates during swing phase, the acceleration data measured on the foot include acceleration of gravity which causes inaccurate calculation of the velocity and the distance. Three gyros are used to compensate the rotation of the sensor system. Moreover, one geomagnetic sensor is employed to derive the heading direction of the subject Healthy volunteers performed ...

• 한국정보통신학회논문지
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• 제15권12호
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• pp.2511-2520
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• 2011

본 논문은 다중 센서 융합의 성능을 높이기 위해 적응형 퍼지-칼만 필터를 적용하고 교차검증법(cross-validation)으로 퍼지시스템 입 출력 소속 함수의 매개변수를 조정하는 방법을 제안한다. 적응형 퍼지-칼만 필터는 가속도의 변화량과 칼만 필터의 잔여오차를 입력으로 시스템잡음, 측정잡음을 추정하여 칼만 이득을 변화시킨다. 적용된 퍼지-칼만 필터는 잡음들을 가우시안 분포로 가정한 이전 방법과 비교하여 비선형/비가우시안 잡음에 강인한 추정 결과를 보여준다. 본 논문에서 제안한 퍼지-칼만 필터를 평가하기 위해 가속도센서/자이로센서를 융합하여 2축 자세추정시스템(Attitude Heading Reference System)을 설계하였고 무인항공기에 사용되는 자세추정센서 NAV420CA-100과 비교하여 성능을 검증하였다.

• 한국정밀공학회지
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• 제26권2호
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• pp.63-70
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• 2009

This paper proposes a novel path finding approach of a mobile robot using RF strength in sensor network. In the experiments based on the proposed method, a mobile robot attempts to find its location, heading direction and the shortest path in the indoor environment. The experimental system consisting of mesh network shares node data and send them to base station. The triangulation and the proposed Grid method calculate the location and heading angle of the robot. In addition, the robot finds the shortest path by using the base station attached on it to receive data of environment around each node. Kalman filter reduces the straight line error when the robot estimates the strength of received signal. The experimental results show the effectiveness of the proposed algorithm.

• 전자공학회논문지B
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• 제31B권2호
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• pp.69-79
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• 1994

The conventional machine vision system which has uniform rectangular grid requires tremendous amount of computation for processing and analysing an image especially in 2-D image transfermations such as scaling, rotation and 3-D reconvery problem typical in robot application environment. In this study, the imaging system with nonuiformly distributed image sensors simulating human visual system, referred to as Ploar Exponential Grid(PEG), is compared with the existing conventional uniform rectangular grid system in terms of image resolution and computational complexity. By mimicking the geometric structure of the PEG sensor cell, we obtained PEG-like images using computer simulation. With the images obtained from the simulation, image resolution of the two systems are compared and some basic image processing tasks such as image scaling and rotation are implemented based on the PEG sensor system to examine its performance. Furthermore Fourier transform of PEG image is described and implemented in image analysis point of view. Also, the range and heading-angle measurement errors usually encountered in 3-D coordinates recovery with stereo camera system are claculated based on the PEG sensor system and compared with those obtained from the uniform rectangular grid system. In fact, the PEC imaging system not only reduces the computational requirements but also has scale and rotational invariance property in Fourier spectrum. Hence the PEG system has more suitable image coordinate system for image scaling, rotation, and image recognition problem. The range and heading-angle measurement errors with PEG system are less than those of uniform rectangular rectangular grid system in practical measurement range.