• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.206-221
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• 2019

Source localization in three-dimensional (3-D) wireless sensor networks (WSNs) is becoming a major research focus. Due to the complicated air-ground environments in 3-D positioning, many of the traditional localization methods, such as received signal strength (RSS) may have relatively poor accuracy performance. Benefit from prior learning mechanisms, fingerprinting-based localization methods are less sensitive to complex conditions and can provide relatively accurate localization performance. However, fingerprinting-based methods require training data at each grid point for constructing the fingerprint database, the overhead of which is very high, particularly for 3-D localization. Also, some of measured data may be unavailable due to the interference of a complicated environment. In this paper, we propose an efficient kernel based 3-D localization algorithm via tensor completion. We first exploit the spatial correlation of the RSS data and demonstrate the low rank property of the RSS data matrix. Based on this, a new training scheme is proposed that uses tensor completion to recover the missing data of the fingerprint database. Finally, we propose a kernel based learning technique in the matching phase to improve the sensitivity and accuracy in the final source position estimation. Simulation results show that our new method can effectively eliminate the impairment caused by incomplete sensing data to improve the localization performance.

• Spatial Information Research
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• v.15 no.2
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• pp.111-121
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• 2007

The GPS positioning offer 3D position using code and carrier phase measurements, but the user can obtain the precise accuracy positioning using carrier phase in Real Time Kinematic(RTK). The main problem, which RTK have to overcome, is the necessary to have a reference station(RS) when using RTK should be generally no more than 10km on average, which is significantly different from DGPS, where distances to RS can exceed several hundred kilometers. The accuracy of today's RTK is limited by the distance dependent errors from orbit, ionosphere and troposphere as well as station dependent influences like multipath and antenna phase center variations. For these reasons, the author proposes Network based GPS Carrier Phase Differential Positioning using Multiple RS which is detached from user receiver about 30km. An important part of the proposed system is algorithm and software development, named DAUNet. The main process is corrections computation, corrections interpolation and searching for the integer ambiguity. Corrections computation of satellite by satellite and epoch by epoch at each reference station are calculated by a Functional model and Stochastic model based on a linear combination algorithm and corrections interpolation at user receiver are used by area correction parameters. As results, the users can obtain the cm-level positioning.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.2
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• pp.67-77
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• 2008

Representation of various types of information in an interactive virtual reality environment on mobile devices had been an attractive and valuable research in this new era. Our main focus is presenting spatial indoor location sensing information in 3D perception in mind to replace the traditional 2D floor map using handheld PDA. Designation of 3D virtual reality by Virtual Reality Modeling Language (VRML) demonstrates its powerful ability in providing lots of useful positioning information for PDA user in real-time situation. Furthermore, by interpolating portal culling algorithm would reduce the 3D graphics rendering time on low power processing PDA significantly. By fully utilizing the CC2420 chipbased sensor nodes, wireless sensor network was established to locate user position based on Received Signal Strength Indication (RSSI) signals. Implementation of RSSI-based indoor tracking method is low-cost solution. However, due to signal diffraction, shadowing and multipath fading, high accuracy of sensing information is unable to obtain even though with sophisticated indoor estimation methods. Therefore, low complexity and flexible accuracy refinement algorithm was proposed to obtain high precision indoor sensing information. User indoor position is updated synchronously in virtual reality to real physical world. Moreover, assignment of magnetic compass could provide dynamic orientation information of user current viewpoint in real-time.

• The KIPS Transactions:PartD
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• v.19D no.3
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• pp.237-246
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• 2012

Although the development of Global Positioning System (GPS) are more and more mature, its accuracy is just acceptable for outdoor positioning, not positioning for the indoor of building and the underpass. For the positioning application area for the indoor of building and the underpass, GPS even cannot achieve that accuracy because of the construction materials while the requirement for accurate positioning in the indoor of building and the underpass, because a space, a person is necessary, may be very small space with several square meters in the indoor of building and the underpass. The Received Signal Strength (RSS) based localization is becoming a good choice especially for the indoor of building and the underpass scenarios where the WiFi signals of IEEE 802.11, Wireless LAN, are available in almost every indoor of building and the underpass. The fundamental requirement of such localization system is to estimate location from Access Point (AP) to mobile device using RSS at a specific location. The Multi-path fading effects in this process make RSS to fluctuate unpredictably, causing uncertainty in localization. To deal with this problem, the combination for the method of Neural Networks and Push-Pull Estimation is applied so that the carried along the devices can learn and make the decision of position using mobile device where it is in the indoor of building and the underpass.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.514-519
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• 2017

In this paper, the pseudorange-based GPS performance using the Android's raw measurements is compared with NMEA. In order to compare the performance between the two different implementations, we used Nexus 9 tablets and collected the raw measurements and NMEA data using the GNSS logger application provided by Google. To verify the performance of the final coordinates calculated, the VRS was used as the reference coordinate and compared with the NMEA results. The resulting horizontal, vertical, and 3D RMS errors of the pseudorange-based GPS using the Android's raw measurements are 3.05, 3.82, and 4.97 m, respectively, which correspond to 32% horizontal, 65% vertical and 49% 3D performance improvement compared with NMEA.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.159-166
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• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• Vacuum Magazine
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• v.3 no.4
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• pp.8-13
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• 2016

The need of space-resolved x-ray photoelectron spectroscopy (XPS) has developed scanning photoelectron microscopy (SPEM). SPEM provides space-resolved XPS data from a spot of a sample as well as images of specific element, chemical state, valency distribution on the surface of a sample. Based on technical advancement of tight x-ray focusing, sample positioning accuracy, and electron analyzer efficiency, SPEM is now capable of providing ~100 nm space resolution for typical XPS functionality, and SPEM has become actively applied for the investigation of chemical state, valency, and electronic structure on the surface of newly discovered materials, such as graphene layers, dichalcogenide 2D-materials, and heterogenous new functional materials.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.201-208
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• 2011

With the increase in the number of smartphone users, precise 3D positional information is required by various applications. The positioning accuracy using civilian single-frequency pseudoranges is at the level of 10 m or so, but most applications these days are asking for a sub-meter level Therefore, instead of an absolute positioning technique, the VRS-based differential approach is applied along with the correction of the double-differenced (DD) residual errors using FKP (Flachen-Korrektur-Parameter). The VRS (Virual Reference Station) is located close to the rover, and the measurements are generated by correcting the geometrical distance to those of the master reference station. Since the unmodeled errors are generally proportional to the length of the baselines, the correction parameters are estimated by fitting a plane to the DD pseudorange errors of the CORS network. The DD positioning accuracy using 24 hours of C/A code measurements provides the RMS errors of 37 cm, 28 cm for latitudinal and longitudinal direction, respectively, and 76 cm for height. The accuracy of the horizontal components is within ${\pm}0.5m$ for about 90% of total epochs, and in particular the biases are significantly decreased to the level of 2-3 cm due to the network-based error modeling. Consequently, it is possible to consistently achieve a sub-meter level accuracy from the single-frequency pseudoranges using the VRS and double-differenced error modeling.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.167-176
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• 1999

The study about quantitative or qualitative analysis of object using digital image is being progressed actively with the development of the image medium and image process technique. But, it is very high that the dependency about image acquisition system of high resolution for image analysis of high accuracy and it is a equipment of high-price. In this study, I extracted the optimum condition of image enhancement by analyzing and enhancing the multiple images which were acquired by system of low-price. And I carried out the analysis of 3D accuracy by being applied the optimum condition of image enhancement. In the result of analysis of average 3D positioning error using law image and enhanced image which is acquired by applying the optimum condition of image enhancement, I could obtain the progressed accuracy about 10％ on the enhanced image.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.382-387
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• 1992

In order to obtain desired arc welding performance, we already developed an arc welding robot system that enabled coordinated motions of dual arm robots. In this system one robot arm holds a welding target as a positioning device, and the other robot moves the welding torch. Concerning to such a dual arm robot system, the positioning accuracy of robots is one important problem, since nowadays conventional industrial robots unfortunately don't have enough absolute accuracy in position. In order to cope with this problem, our robot system employed teaching playback method, where absolute error are compensated by the operator's visual feedback. Due to this system, an ideal arc welding considering the posture of the welding target and the directions of the gravity has become possible. Another problem still remains, while we developed an original teaching method of the dual arm robots with coordinated motions. The problem is that manual teaching tasks are still tedious since they need fine movements with intensive attentions. Therefore, we developed a 3-dimensional vision guided robot control method for our welding robot system with coordinated motions. In this paper we show our 3-dimensional vision sensor to guide our arc welding robot system with coordinated motions. A sensing device is compactly designed and is mounted on the tip of the arc welding robot. The sensor detects the 3-dimensional shape of groove on the target work which needs to be weld. And the welding robot is controlled to trace the grooves with accuracy. The principle of the 3-dimensional measurement is depend on the slit-ray projection method. In order to realize a slit-ray projection method, two laser slit-ray projectors and one CCD TV camera are compactly mounted. Tactful image processing enabled 3-dimensional data processing without suffering from disturbance lights. The 3-dimensional information of the target groove is combined with the rough teaching data they are given by the operator in advance. Therefore, the teaching tasks are simplified