• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.63-67
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• 2016

Recently, BLE beacons are widely used in indoor precision positioning systems because of their low battery consumption and low infrastructure cost. However, existing BLE beacon based indoor positioning algorithms are difficult to compensate for position errors due to the user's moving speed. Therefore, we proposed a position error correction algorithm that combines bounced cancellation and minimum distance maintenance algorithm with a positioning error correction method using direction vectors. Experimental results show that the proposed algorithm guarantees superior positioning performance than the existing indoor positioning algorithm and also improves the performance of position error compensation.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.774-781
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• 2003

The important factors that cause position error in X-Y robot are inertial force, frictions and spring distortion in screw or coupling. We have to estimate these factors precisely to correct position errors, Which is very difficult. In this paper, we makes systems to inspect metal stencil which is used to print solder paste on pads of SMD of PCB with low precision X-Y robot and vision system. To correct position error that is caused by low precision X-Y robot, we defines position error vector that is formed with position of objects that exist in reference and camera image. We apply MHT(Modified Hough Transformation) for the aim of determining the dominant position error vector. We modify reference image using extracted dominant position error vector and obtain reference image that is the same with camera image. Effectiveness and performance of this method are verified by simulation and experiment.

• Journal of the Korea Computer Graphics Society
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• v.3 no.2
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• pp.35-43
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• 1997

In monitor-based AR(Augmented Reality) systems, it is required to know the position and direction of a camera in order to combine real images from a camera with virtual images exactly_ Because a tracker is parted from a camera, however, there is a registration error caused by the inconsistency of a tracker with a camera. In this paper, we describe the error correction method using genetic algorithm. This method looks for the position and direction of a camera using genetic algorithm and solves the error correction matrix of it. And then it is registered of the real images and the revised virtual image. It has an effect on the error correction caused by the misalignment of a tracker with a camera in complex AR systems.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.533-535
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• 2006

Cleaning robot that is selling in present city has various cleaning algorithm. However, error of most products happens on progress direction by small obstacle that do not properly and miss cleaning thereby happens. There is robot that correct own position, but is hard to use in general home because economical strain is very big because is high price product very. In this paper measures angular velocity of robot using deviation sensor, and do to correct error using turning angular velocity and vertical angular velocity. Because detailed cleaning such as high pice style is available without addition of expensive hardware in middle and low price style cleaning product thereby, can possess price competitive power.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.824-833
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• 2006

In this paper, the image modelling of road's lane markings is established using view frustum(VF) model. From this model, a measurement system of lane markings and obstacles is proposed. The system also involve the real time processing of the 3D position coordinate and the distance data from the camera to the points on the 3D world coordinate by virtue of the camera calibration. In order to reduce their measurement error, an useful algorithm for which analyze the geometric variations due to traveling vehicle's fluctuation using VF model is proposed. In experiments, without correction, for instance, the $0.4^{\circ}$ of pitching rotation gives the error of $0.4{\sim}0.6m$ at the distance of 10m, but the more far distance cause exponentially the more error. We con finned that this algorithm can be reduced less than 0.1m of error at the same condition.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.3-7
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• 1999

The images of the meteorological satellite NOAA contain geometrical distortions caused by its ambiguous position, its vibration, its sensor's movement, and so on. Geometric correction of satellite images is one of the most important parts in many remote sensing as the primary processing. Ground control points (GCP's) are necessary to check the accuracy of geometric correction and used for precise geometric correction. In this paper, a method for automatically selecting the residual error is presented. Calculating the effective angle and residual errors vector using the succeeded matching GCP's, precise geometric correction using an affine transformation is applied to systematically a corrected image. And the error is decreased by an affine transformation. The above enable the geometric correction of high quality.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.229-230
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• 2012

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.280-286
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• 2022

In order to efficiently collect data, it is essential to locate the facilities and analyze the movement data. The current technology for location collection can collect data using a GPS sensor, but GPS has a strong straightness and low diffraction and reflectance, making it difficult for indoor positioning. In the case of indoor positioning, the location is determined by using wireless network technologies such as Wifi, but there is a problem with low accuracy as the error range reaches 20 to 30 m. In this paper, using BLE 4.2 built in Raspberry Pi, we implement Bluetooth Smart Ready. In detail, a beacon was produced for Advertise, and an experiment was conducted to support the serial port for data transmission/reception. In addition, advertise mode and connection mode were implemented at the same time, and a 3-count gradual algorithm and a quadrangular positioning algorithm were implemented for Bluetooth RSSI error correction. As a result of the experiment, the average error was improved compared to the first correction, and the error rate was also improved compared to before the correction, confirming that the error rate for position measurement was significantly improved.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.1
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• pp.118-128
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• 2017

In this study, we propose a real time inertial navigation system/global positioning system (INS/GPS) integrated smoothing algorithm based on an extended Kalman filter (EKF) and a position damping loop (PDL) for synthetic aperture radar (SAR). Integrated navigation algorithms usually induce discontinuities due to error correction update by the Kalman filter, which are as detrimental to the performance of SAR as the relative position error. The proposed smoothing algorithm suppresses these discontinuities and also reduces the relative position error in real time. An EKF estimates the navigation errors and sensor biases, and all the errors except for the position error are corrected directly and instantly. A PDL activated during SAR operation period imposes damping effects on the position error estimates, where the estimated position error is corrected smoothly and gradually, which contributes to the real time smoothing and small relative position errors. The residual errors are re-estimated by the EKF to maintain the estimation performance and the stability of the overall loop. The performance improvements were confirmed by Monte Carlo simulations. The simulation results showed that the discontinuities were reduced by 99.8% and the relative position error by 48% compared with a conventional EKF without a smoothing loop, thereby satisfying the basic performance requirements for SAR operation. The proposed algorithm may be applicable to low cost SAR systems which use a conventional INS/GPS without changing their hardware configurations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4971-4987
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• 2019

Node localization is the basic task of underwater wireless sensor networks (UWSNs). Most of the existing underwater localization methods rely on ranging accuracy. Due to the special environment conditions in the ocean, beacon nodes are difficult to deploy accurately. The narrow bandwidth and high delay of the underwater acoustic communication channel lead to large errors. In order to reduce the ranging error and improve the positioning accuracy, we propose a localization algorithm based on ranging correction and inertial coordination. The algorithm can be divided into two parts, Range Correction based Localization algorithm (RCL) and Inertial Coordination based Localization algorithm (ICL). RCL uses the geometric relationship between the node positions to correct the ranging error and obtain the exact node position. However, when the unknown node deviates from the deployment area with the movement of the water flow, it cannot communicate with enough beacon nodes in a certain period of time. In this case, the node uses ICL algorithm to combine position data with motion information of neighbor nodes to update its position. The simulation results show that the proposed algorithm greatly improves the positioning accuracy of unknown nodes compared with the existing localization methods.