• Journal of the Korea Institute of Information and Communication Engineering
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• 제19권10호
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• pp.2307-2314
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• 2015

This paper focuses on the generation algorithm of BeiDou pseudorange correction (PRC) and simulation based performance verification for design of Differential Global Navigation Satellite System (DGNSS) reference station and integrity monitor (RSIM) in order to prepare for recapitalization of DGNSS. First of all, it discusses the International standard on DGNSS RSIM, based on the interface control document (ICD) for BeiDou, estimates the satellite position using satellite clock offset and user receiver clock offset, and the system time offset between Global Positioning System (GPS) and BeiDou. Using the performance verification platform interfaced with GNSS (GPS/BeiDou) simulator, it calculates the BeiDou pseudorange corrections , compares the results of position accuracy with GPS/DGPS. As the test results, this paper verified to meet the performance of position accuracy for DGNSS RSIM operation required on Radio Technical Commission for Maritime Services (RTCM) standard.

• Journal of the Institute of Convergence Signal Processing
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• 제5권4호
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• pp.256-262
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• 2004

A key component of an autonomous mobile robot is to localize itself and build a map of the environment simultaneously. In this paper, we propose a vision-based localization and mapping algorithm of mobile robot using fisheye lens. To acquire high-level features with scale invariance, a camera with fisheye lens facing toward to ceiling is attached to the robot. These features are used in mP building and localization. As a preprocessing, input image from fisheye lens is calibrated to remove radial distortion and then labeling and convex hull techniques are used to segment ceiling and wall region for the calibrated image. At the initial map building process, features we calculated for each segmented region and stored in map database. Features are continuously calculated for sequential input images and matched to the map. n some features are not matched, those features are added to the map. This map matching and updating process is continued until map building process is finished, Localization is used in map building process and searching the location of the robot on the map. The calculated features at the position of the robot are matched to the existing map to estimate the real position of the robot, and map building database is updated at the same time. By the proposed method, the elapsed time for map building is within 2 minutes for 50㎡ region, the positioning accuracy is ±13cm and the error about the positioning angle of the robot is ±3 degree for localization.

• Journal of IKEEE
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• 제9권1호
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• pp.7-18
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• 2005

A key component of an autonomous mobile robot is to localize itself accurately and build a map of the environment simultaneously. In this paper, we propose a vision-based mobile robot localization and mapping algorithm using scale-invariant features. A camera with fisheye lens facing toward to ceiling is attached to the robot to acquire high-level features with scale invariance. These features are used in map building and localization process. As pre-processing, input images from fisheye lens are calibrated to remove radial distortion then labeling and convex hull techniques are used to segment ceiling region from wall region. At initial map building process, features are calculated for segmented regions and stored in map database. Features are continuously calculated from sequential input images and matched against existing map until map building process is finished. If features are not matched, they are added to the existing map. Localization is done simultaneously with feature matching at map building process. Localization. is performed when features are matched with existing map and map building database is updated at same time. The proposed method can perform a map building in 2 minutes on $50m^2$ area. The positioning accuracy is ${\pm}13cm$, the average error on robot angle with the positioning is ${\pm}3$ degree.

• Journal of Broadcast Engineering
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• 제9권4호
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• pp.411-423
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• 2004

In Korea, Eureka-147 DAB (Digital Audio Broadcasting) temporarily decided as the standard system for digital audio broadcasting was evolved into DMB (Digital Multimedia Broadcasting) to complement the technical vulnerability in mobile reception of terrestrial DTV. According to introducing video service in T-DMB (Terrestrial DMB), 'Terrestrial DMB Experimental Broadcasting for Video Service', a national project of the MIC (Ministry of Information and Communication), was done for verifying the possibility of video service via T-DMB. The main objective of the project is computing the effective field strength and coverage for making a plan to build T-DMB broadcasting network and developing transmitting and receiving equipment. In case of digital broadcasting, it is absolutely essential to measure BER (Bit Error Rate) and electric field strength in order to evaluate coverage and quality of received signal. In this paper, we implement an integrated mobile measurement system for T-DMB. For this purpose, we propose efficient data structure and algorithm for BER measurement. By adding GPS (Global Positioning System) and electric field strength measurement parts into BER measurement part, we complete the integrated mobile measurement system, and then verify it by experiments and field tests. The developed system was used in a national project, 'Terrestrial DMB Experimental Broadcasting for Video Service' and measurement results will be used as fundamental data for building T-DMB broadcasting network.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제32권1D호
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• pp.81-88
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• 2012

This present research was carried out by dividing two parts; field surveying and data processing, in order to analyze changed patterns of a shoreline. Firstly, the shoreline information measured by the precise GPS positioning during long duration was collected. Secondly, the algorithm for detecting an auto boundary with regards to the changed shoreline with multi-image data was developed. Then, a comparative research was conducted. Haeundae beach which is one of the most famous ones in Korea was selected as a test site. RTK-GPS surveying had been performed overall eight times from September 2005 to September 2009. The filed test by aerial Lidar was conducted twice on December 2006 and March 2009 respectively. As a result estimated from both sensors, there is a slight difference. The average length of shoreline analyzed by RTK-GPS is approximately 1,364.6 m, while one from aerial Lidar is about 1,402.5 m. In this investigation, the specific algorithm for detecting the shoreline detection was developed by Visual C++ MFC (Microsoft Foundation Class). The analysis result estimated by aerial photo and satellite image was 1,391.0 m. The level of reliability was 98.1% for auto boundary detection when it compared with real surveying data.

• Journal of the Korean Society of Radiology
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• 제13권7호
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• pp.901-907
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• 2019

The aim of this study is to evaluate the ability of target localizations of Leksell GammaPlan(LGP) in Gamma Knife Subthalamotomy(or Pallidotomy, Thalamotomy) of functional diseases. To evaluate the accuracy of LGP's location settings, the difference Δr of the target coordinates calculated by LGP (or LSP) and author's algorithm was reviewed for 10 patients who underwent Deep Brain Stimulation(DBS) surgery. Δr ranged from 0.0244663 mm to 0.107961 mm. The average of Δr was 0.054398 mm. Transformation matrix between stereotactic space and brain atlas space was calculated using PseudoInverse or Singular Value Decomposition of Mathematica to determine the positional relationship between two coordinate systems. Despite the precise frame positioning, the misalignment of yaw from -3.44739 degree to 1.82243 degree, pitch from -4.57212 degree to 0.692063 degree, and rolls from -6.38239 degree to 7.21426 degree appeared. In conclusion, a simple in-house algorithm was used to test the accuracy for location settings of LGP(or LSP) in Gamma Knife platform and the possibility for Gamma Knife Subthalamotomy. The functional diseases can be treated with Gamma Knife Radiosurgery with safety and efficacy. In the future, the proposed algorithm for target localizations' QA will be a great contributor to movement disorders' treatment of several Gamma Knife Centers.

• Korean Journal of Remote Sensing
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• 제27권5호
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• pp.507-520
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• 2011

Conventional radar altimeter system measured directly the distance between the satellite and the ocean surface and frequently used by aircraft for approach and landing. The radar altimeter is good at flat surface like sea whereas it is difficult to determine precise three dimensional ground coordinates because the ground surface, unlike ocean, is very indented. To overcome this drawback of the radar altimeter, we have developed and validated the interferometric radar altimeter signal processing which is combined with new synthetic aperture and interferometric signal processing algorithm to extract precise three-dimensional ground coordinates. The proposed algorithm can accurately measure the three dimensional ground coordinates using three antennas. In a set of 70 simulations, the averages of errors in x, y and z directions were approximately -0.40 m, -0.02 m and 4.22 m, respectively and the RMSEs were about 3.40 m, 0.30 m and 6.20 m, respectively. The overall results represent that the proposed algorithm is effective for accurate three dimensional ground positioning.

• Journal of Advanced Marine Engineering and Technology
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• 제40권9호
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• pp.836-841
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• 2016

An indoor positioning system using Wi-Fi is essential to produce a radio map that combines the indoor space of two or more dimensions, the information of node positions, and etc. in processing for constructing the radio map, the measurement of the received signal strength indicator(RSSI) and the confirmation of node placement information counsume substantial time. Especially, when the installed wireless environment is changed or a new space is created, easy installation of the node and fast indoor radio mapping are needed to provide indoor location-based services. In this paper, to reduce the time consumption, we propose an algorithm to distinguish the straight and curve lines of a corridor section by RSSI visualization and Sobel filter-based edge detection that enable accurate node deployment and space analysis using cable-type Wi-Fi node installed at a 3 m interval. Because the cable type Wi-Fi is connected by a same power line, it has an advantage that the installation order of nodes at regular intervals could be confirmed accurately. To be able to analyze specific sections in space based on this advantage, the distribution of the signal was confirmed and analyzed by Sobel filter based edge detection and total RSSI distribution(TRD) computation through a visualization process based on the measured RSSI. As a result to compare the raw data with the performance of the proposed algorithm, the signal intensity of proposed algorithm is improved by 13.73 % in the curve section. Besides, the characteristics of the straight and the curve line were enhanced as the signal intensity of the straight line decreased by an average of 34.16 %.

• Journal of Korea Spatial Information System Society
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• 제10권3호
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• pp.55-65
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• 2008

For obtaining telematics traffic information(travel time or speed in an individual link), there are many kinds of devices to collect traffic data. Since the GPS satellite signals have been released to civil society, thank to the development of GPS technology, the GPS has become a very useful instrument for collecting traffic data. GPS can reduce the cost of installation and maintenance in contrast with existing traffic detectors which must be stationed on the ground. But. there are Problems when GPS data is applied to the existing filtering techniques used for analyzing the data collected by other detectors. This paper proposes a method to provide users with correct traffic information through filtering abnormal data caused by the unusual driving in collected data based on GPS. We have developed an algorithm that can be applied to real-time GPS data and create more reliable traffic information, by building patterns of past data and filtering abnormal data through selection of filtering areas using Quartile values. in order to verify the proposed algorithm, we experimented with actual traffic data that include probe cars equipped with a built-in GPS receiver which ran through Gangnam Street in Seoul. As a result of these experiments, it is shown that link travel speed data obtained from this algorithm is more accurate than those obtained by existing systems.

• Korean Journal of Remote Sensing
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• 제38권6_1호
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• pp.1057-1068
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• 2022

This paper compares the combination performance of feature point-based matching algorithms as a study to confirm the matching possibility between image taken by a user and a virtual texture image with the goal of developing mobile-based real-time image positioning technology. The feature based matching algorithm includes process of extracting features, calculating descriptors, matching features from both images, and finally eliminating mismatched features. At this time, for matching algorithm combination, we combined the process of extracting features and the process of calculating descriptors in the same or different matching algorithm respectively. V-World 3D desktop was used for the virtual indoor texture image. Currently, V-World 3D desktop is reinforced with details such as vertical and horizontal protrusions and dents. In addition, levels with real image textures. Using this, we constructed dataset with virtual indoor texture data as a reference image, and real image shooting at the same location as a target image. After constructing dataset, matching success rate and matching processing time were measured, and based on this, matching algorithm combination was determined for matching real image with virtual image. In this study, based on the characteristics of each matching technique, the matching algorithm was combined and applied to the constructed dataset to confirm the applicability, and performance comparison was also performed when the rotation was additionally considered. As a result of study, it was confirmed that the combination of Scale Invariant Feature Transform (SIFT)'s feature and descriptor detection had the highest matching success rate, but matching processing time was longest. And in the case of Features from Accelerated Segment Test (FAST)'s feature detector and Oriented FAST and Rotated BRIEF (ORB)'s descriptor calculation, the matching success rate was similar to that of SIFT-SIFT combination, while matching processing time was short. Furthermore, in case of FAST-ORB, it was confirmed that the matching performance was superior even when 10° rotation was applied to the dataset. Therefore, it was confirmed that the matching algorithm of FAST-ORB combination could be suitable for matching between virtual texture image and real image.