• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.544-550
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• 2008

In this paper, an efficient positioning algorithm is proposed for a local positioning system using ultrasound and RF in WSN. The proposed positioning algorithm is the modified Savarese method where measurement noise characteristics are included as a weighting. Furthermore the ill-conditioned and the singularity problem occurred when all beacons are installed at the same height are removed. And the method is applicable to 2D positioning with 2 beacons only. The experiments with implemented system show the accurate seamless positioning less than 2cm error both static and dynamic experiments while the original Savarese method can not provide positions.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.795-800
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• 2008

The paper presents research for the established experiment environment of multi vehicle robot, localization algorithm that is based on vehicle control, and path tracking. The established experiment environment consists of ultrasonic positioning system, vehicle robot, server and wireless module. Ultrasonic positioning system measures positioning for using ultrasonic sensor and generates many errors because of the influence of environment such as a reflection of wall. For a solution of this fact, localization algorithm is proposed to determine a location using vehicle kinematics and selection of a reliable location data. And path tracking algorithm is proposed to apply localization algorithm and LOS, finally, that algorithms are verified via simulation and experimental

• 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.

• Imaging Science in Dentistry
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• v.48 no.4
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• pp.245-254
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• 2018

Purpose: To assess the effects of object position in the field of view (FOV) and application of a metal artifact reduction (MAR) algorithm on the diagnostic accuracy of cone-beam computed tomography (CBCT) for the detection of vertical root fractures(VRFs). Materials and Methods: Sixty human single-canal premolars received root canal treatment. VRFs were induced in 30 endodontically treated teeth. The teeth were then divided into 4 groups, with 2 groups receiving metal posts and the remaining 2 only having an empty post space. The roots from different groups were mounted in a phantom made of cow rib bone, and CBCT scans were obtained for the 4 different groups. Three observers evaluated the images independently. Results: The highest frequency of correct diagnoses of VRFs was obtained with the object positioned centrally in the FOV, using the MAR algorithm. Peripheral positioning of the object without the MAR algorithm yielded the highest sensitivity for the first observer (66.7%). For the second and third observers, a central position improved sensitivity, with or without the MAR algorithm. In the presence of metal posts, central positioning of the object in the FOV significantly increased the diagnostic sensitivity and accuracy compared to peripheral positioning. Conclusion: Diagnostic accuracy was higher with central positioning than with peripheral positioning, irrespective of whether the MAR algorithm was applied. However, the effect of the MAR algorithm was more significant with central positioning than with peripheral positioning of the object in the FOV. The clinical experience and expertise of the observers may serve as a confounder in this respect.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.1
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• pp.15-24
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• 2018

This study analyzed positioning accuracy of the multi-differential global navigation satellite system (DGNSS) algorithm that integrated GPS, GLONASS, and BDS. Prior to the analysis, four sites of which satellite observation environment was different were selected, and satellite observation environments for each site were analyzed. The analysis results of the algorithm performance at each of the survey points showed that high positioning performance was obtained by using DGPS only without integration of satellite navigation systems in the open sky environment but the positioning performance of multi-DGNSS became higher as the satellite observation environments degraded. The comparison results of improved positioning performance of the multi-DGNSS at the poor reception environment compared to differential global positioning system (DGPS) positioning results showed that horizontal accuracy was improved by 78% and vertical accuracy was improved by 65% approximately.

• Journal of Biosystems Engineering
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• v.36 no.2
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• pp.116-121
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• 2011

This study was conducted to develop a robust navigator which could be in positioning for precision farming through developing a plural GPS receiver with 4 sets of GPS antenna. In order to improve positioning accuracy by integrating GPS signals received simultaneously, the algorithm for processing plural GPS signal effectively was designed. Performance of the algorithm was tested using a simulation program and a fixed point on WGS 84 coordinates. Results of this study are aummarized as followings. 1. 4 sets of lower grade GPS receiver and signals were integrated by kalman filter algorithm and geometric algorithm to increase positioning accuracy of the data. 2. Prototype was composed of 4 sets of GPS receiver and INS components. All Star which manufactured by CMC, gyro compass made by KVH, ground speed sensor and integration S/W based on RTOS(Real Time Operating System)were used. 3. Integration algorithm was simulated by developed program which could generate random position error less then 10 m and tested with the prototype at a fixed position. 4. When navigation data was integrated by geometrical correction and kalman filter algorithm, estimated positioning erros were less then 0.6 m and 1.0 m respectively in simulation and fixed position tests.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.551-560
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• 2011

Recently, There has been increasing concern about WLAN-based indoor positioning system. Most of the existing WLAN-based positioning systems use a fingerprinting method as a main approach. In the fingerprinting approach, the accuracy of the location of a mobile objects is proportional to the number of reference points. However, depending on the increasing number of reference points in the training phase, it requires more time and effort to create fingerprint database. To solve these problems, we propose the new indoor positioning algorithm that calculate the distance between a mobile objects and an AP using the information of surrounding environment WLAN based APs and applied the particle filter to the proposed algorithm in order to improve the accuracy of the estimated location in this paper. To implement this algorithm, at first environmental information database such as wall, iron door, glass door, partition etc. existing in the periphery of the AP should be established. The positioning use attenuation model and path loss model. Our experimental results with proposed algorithm are verified that the positioning accuracy was low but solved the problems with fingerprinting, compared with other positioning algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.101-108
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• 2019

Due to recent improvements in computer processing speed and image processing technology, researches are being actively carried out to combine information from camera with existing GNSS (Global Navigation Satellite System) and dead reckoning. In this study, developed a vision-based positioning assistant algorithm to estimate the distance to the object from stereo images. In addition, GNSS/on-board vehicle sensor/vision based positioning algorithm is developed by combining vision based positioning algorithm with existing positioning algorithm. For the performance analysis, the velocity calculated from the actual driving test was used for the navigation solution correction, simulation tests were performed to analyse the effects of velocity precision. As a result of analysis, it is confirmed that about 4% of position accuracy is improved when vision information is added compared to existing GNSS/on-board based positioning algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.130-136
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• 2005

This paper presents an optimal design and the performance evaluation of two-axis nano positioning stage with round notched flexure hinges. A flexure hinge mechanism with round notched flexure hinges is to guide the linear motions of a moving plate in the nano positioning stage. A Min-Max algorithm is applied to the design of the flexure hinge mechanism for nano positioning stage. In the design process, the structure of the flexure hinge mechanism is fixed, then the radius of a round hole and the width of two round holes are chosen as design variables, and finally the do sign variables are calculated by the Min-Max algorithm. The machined flexure hinge mechanism, stack type PZTs for actuation and capacitance type displacement sensors for position measurement are assembled into the nano positioning stage. The experimental results of the manufactured nano positioning stage show the first modal resonance frequency of 197 Hz, the operating range of 40 um, and the resolution of 3 nm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.343-364
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• 2021

In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.