Coordinates Of Reference Points Research Articles

Vertical Accuracy of Google Earth Data

Digital Elevation Models (DEMs) are an important data source used in many engineering and Geographic Information System (GIS) applications. This paper illustrates a strategy for creating a DEM by utilizing elevation data from Google Earth and evaluating the vertical positional accuracy of the generated DEM adopting a well-defined methodology. To ensure the accuracy of the elevation data obtained from Google Earth, a thorough evaluation was done in three diverse small districts of the northern shoreline in Egypt. The evaluation process involved determining the ground coordinates of reference points utilizing two surveying techniques: total station and Real-Time Kinematic (RTK) Global Positioning System (GPS) surveys. These coordinates were compared with the ones predicated by the DEM generated by putting into service Google Earth's elevation data. Furthermore, the vertical accuracy was assessed using Shuttle Radar Topographic Mission (SRTM) data of Google Earth collected at two different periods in 2015 and 2023. The vertical accuracy of the Google Earth data is detailed utilizing Mean Error (ME), Maximum Absolute Error (MAE), and Root Mean Square Error (RMSE). According to the results, Google Earth's elevation data accuracy remains consistent from 2015 to 2023, and refining SRTM data does not improve the vertical accuracy. The vertical accuracy of the total station survey surpasses the one of the RTK GPS survey, and the elevation accuracy of the RTK GPS survey decreases with increasing height difference. In addition, the vertical accuracy of DEMs was found to be sufficient for some engineering applications but not accurate enough for precise engineering studies. The accuracy achieved in small height difference terrain can be utilized to produce large-scale cadastral maps, city plans, or land use maps. Finally, the elevation data offered by Google Earth can be utilized for preliminary studies at a low cost. However, to ensure the accuracy of these data, it is recommended that users compare them with reference data before implementation.

Identification of wheel track in the wheat field

Agriculture machinery navigating along permanent traffic lanes in the farmland may avoid causing extensive soil compaction. However, the permanent traffic lanes are frequently covered up or eliminated by following tillage practices. It is necessary to identify the wheel tracks designed as permanent traffic lanes in order to ensure the agriculture machinery travels along the designated wheel tracks when cultivating the field. This study proposed an identification method of wheel tracks based on the morphological characteristics of wheel tracks and the environmental conditions around the wheel tracks in the wheat fields. The proposed method first utilized the maximum interclass variance to identify the contours of the main part of the wheel track and the shadow regions around the wheel track’s edges. The main part of the wheel tracks was then separated from interference pixels by moving the centerline of the main part of the wheel track, which was derived by skeleton algorithm and curve fitting, towards the right or left edge of the wheel track at a specific distance. In a morphological opening operation, specific linear and circular structural elements were used to segment the shadow regions along the edge of the wheel track. The remaining wheel track was finally recognized by computing the complement of the region identified. After achieving the segmentation of wheel tracks, many reference points near the outside of the wheel track edge in the original image were chosen as fiducial points for evaluating the differences between the actual value and the recognized wheel track edge. The evaluation was based on computing the root mean squared error (RMSE) and the mean absolute error (MAE) of coordinates of reference points and recognized wheel track edge. The results showed that the largest RMSE and MAE were 24.01 pixels (0.0045 m) and 17.32 pixels (0.0032 m), respectively. The low values of RMSE and MAE reveal that the accuracy of the algorithm developed in this study is high, and using this algorithm may segment the wheel track in the wheat field accurately.

ANALYSIS OF CALIBRATION ERRORS IN AUTOMOBILE CONTROL TELEVISION SYSTEM

Camera calibration is a critical method for 3D measurement applications based on 2D images. During calibration, internal camera parameters such as principal point and focal length are determined. The principal point is the intersection of the camera's optical axis and the image plane, while the focal length is measured from the lens center to the principal point.This article theoretically investigates calibration errors in two reference planes considering various conditions, such as shifts in the reference plane and changes in focal lengths. Errors in determining the coordinates of reference points in images were used to evaluate these calibration errors.The error in estimating the focal length and principal point is formulated using analytical equations, and the results are compared with simulation outcomes to validate the effectiveness of the proposed formulas. The research reveals that calibration errors arise due to shifts in the reference plane and changes in focal lengths. The obtained results are crucial for enhancing camera calibration methods and improving the accuracy of 3D measurements based on 2D images.This article extends the understanding of camera calibration errors and provides new theoretical approaches for their assessment. The research findings may be beneficial for scientists and practitioners working in the fields of computer vision, image processing, and 3D measurements.Further research in this area may contribute to the development of new calibration methods and approaches that will improve the performance of automotive systems and ensure high accuracy and reliability in the future.

Application of Bezier curves for description of structure shape in optimization of adhesive joints

The problem of topological optimization of a symmetrical double-shear adhesive joint has been solved. The suggested mathematical model of a joint with variable thickness generalizes the classic Holland–Reissner model. The shape of the doubler is described by means of the Bezier curve. Seeking parameters in the optimization problem are coordinates of reference points of the Bezier curve. Both joint length and doubler cross-section area can be considered an objective function. The restriction is applied on stress in adhesive film and doubler. The direct problem of finding the joint stress state at given geometric parameters was solved using the finite difference method. The genetic algorithm was used to solve the optimization problem. In order to improve the convergence of the genetic algorithm, the island model of evolution is suggested, which ensures quick evolution selection and stability of obtained results. The model problem is solved.

IPos-5G: Indoor Positioning via Commercial 5G NR CSI

The fifth-generation (5G) networks have been massively deployed in commerce. The new features introduced by 5G networks are beneficial to wireless positioning. In this study, the performance of indoor positioning with commercial 5G new radio (NR) signals is investigated, and the channel state information (CSI) extracted from the downlink synchronization signal block is utilized. Considering the limited 5G NR base station (known as gNodeB) is hearable indoors, the fingerprint method is used, and an indoor positioning system termed iPos-5G is developed. The system consists of four components. Firstly, a module of quality control is applied for CSI preprocessing. Secondly, an unsupervised deep-autoencoder network is utilized to reconstruct CSI features. Thirdly, by supervised learning, a radial basis function is improved to optimize the probability model for similarity calculations. Finally, an amplitude-phase probability fusion function is proposed for positioning by weighting the coordinates of reference points. To verify the effectiveness of iPos-5G, indoor field tests are carried out in the scenarios of an office and a corridor. The test results show that iPos-5G achieves mean absolute errors of 2.14 and 2.81 m and standard deviation of the errors of 1.07 and 1.66 m, which outperforms the compared CSI fingerprint methods in terms of positioning accuracy and stability.

Computer-Aided Assessment of Three-Dimensional Standard Bone Morphology of the Distal Radius.

The present study attempted to define the three-dimensional (3D) locations of reference points and standard measures of the distal radius of a normal wrist joint. One hundred wrists from 50 males and 50 females who matched the age distribution (19-95 years old, mean: 56.0 years old) were evaluated. Computed tomography (CT) images of normal wrist joints acquired for comparison with the affected side were used. The absence of a previous history and complaints in the unaffected wrist was confirmed in an interview and with medical records. Three-dimensional images of the distal radius were reconstructed using the data obtained from CT scans. The site at which the major axis of the radial diaphysis contacted the distal radius joint surface was defined as the origin. The 3D coordinates of reference points for the radial styloid process (1), sigmoid notch volar edge (2), and sigmoid notch dorsal edge (3) as well as the barycenter for the joint surface and joint surface area were evaluated. A slope of the line connecting coordinates 1-2 in the coronal plane was evaluated as the 3D radial inclination (3DRI) and that connecting coordinates 2-3 in the sagittal plane as the 3D palmar tilt (3DPT). Each measurement value was compared between males and females. The positions of each reference point from the origin were as follows: (1) 14.2 ± 1.3/12.6 ± 1.1 mm for the distal-palmar-radial position; (2) 19.3 ± 1.3/16.9 ± 1.3 mm for the proximal-palmar-ulnar position; (3) 15.6 ± 1.4/14.1 ± 0.9 mm for the proximal-dorsal-ulnar position; and (barycenter) 4.1 ± 0.7/3.7 ± 0.7 mm for the proximal-volar-ulnar position for males and females, respectively. The areas of the radius articular surface were 429.0 ± 67.9/347.6 ± 44.6 mm2 for males and females, respectively. The 3DRI and 3DPT were 24.2 ± 4.0/25.7 ± 3.1° and 10.9 ± 5.1/13.2 ± 4.4° for males and females, respectively. Significant differences were observed in all measurement values between males and females (p < 0.01). The reference points and measured values obtained in the present study will serve as criteria for identifying the dislocation direction and reduction conditions of distal radius fractures in 3D images.

A method for locating abnormal sound in transmission line channels based on time delay estimation and equipment coordinates

To get rid of the current transmission line visual monitoring device which only relies on a single photo-monitoring method, this paper proposes a method based on time-delay estimation and equipment coordinates to locate abnormal sound in the transmission line channel. Firstly, the audio-visual equipment is selected to collect the abnormal sound information of any transmission line as the reference warning record, and the relative time difference between other warning records and the reference warning record is determined. Then, the corresponding audio-visual equipment of the reference alarm record is used as a reference point to set up a Cartesian coordinate system, obtain the GPS information of other audio-visual equipment, unify the GPS information, and get the coordinates of other audio-visual equipment; finally, based on the reference point coordinates, other audio-visual equipment coordinates, and the relative time difference, the transmission channel abnormal sound source coordinates are obtained. Through the experiment of firecracker sound, we can get the firecracker sound within 2km in the open environment, which proves that the location method can effectively enhance the monitoring effect of the transmission channel.

A Deep-Learning Extraction Method for Orchard Visual Navigation Lines

Orchard machinery autonomous navigation is helpful for improving the efficiency of fruit production and reducing labor costs. Path planning is one of the core technologies of autonomous navigation for orchard machinery. As normally planted in straight and parallel rows, fruit trees are natural landmarks that can provide suitable cues for orchard intelligent machinery. This paper presents a novel method to realize path planning based on computer vision technologies. We combine deep learning and the least-square (DL-LS) algorithm to carry out a new navigation line extraction algorithm for orchard scenarios. First, a large number of actual orchard images are collected and processed for training the YOLO V3 model. After the training, the mean average precision (MAP) of the model for trunk and tree detection can reach 92.11%. Secondly, the reference point coordinates of the fruit trees are calculated with the coordinates of the bounding box of trunks. Thirdly, the reference lines of fruit trees growing on both sides are fitted by the least-square method and the navigation line for the orchard machinery is determined by the two reference lines. Experimental results show that the trained YOLO V3 network can identify the tree trunk and the fruit tree accurately and that the new navigation line of fruit tree rows can be extracted effectively. The accuracy of orchard centerline extraction is 90.00%.

Accuracy of Maxillary Positioning During Orthognathic Surgery: A Comparison of Web-based 3-Dimensional Virtual Surgical Planning and Actual Outcomes.

To determine the accuracy of planned maxillary positioning by virtual surgery by comparing planned and actual postoperative outcomes. Twenty patients who underwent 2-jaw orthognathic surgery performed by a single surgeon from May 2017 to December 2020 were the subjects of this retrospective study. The coordinates of reference points in horizontal, sagittal, and coronal planes as determined by virtual surgery were compared with those of actual surgical outcomes. The reference points used were as follows: #16 mesiobuccal cusp tip (#16), #26 mesiobuccal cusp tip (#26), and #11 mesial tip (U1); anterior nasal spine; and posterior nasal spine. Three-dimensional linear distances between the reference point on which virtual surgery was performed and the reference point after the actual operation was calculated. Of the 20 patients, there were 11 males and 9 females of average age 20.65±2.41 years. Three-dimensional printed wafers had high accuracy with a maximum difference of 0.3mm. No significant difference was observed in horizontal or coronal planes for any reference point, but a significant difference was observed in the sagittal plane. However, positional differences between planned and actual reference points were all <1mm. Virtual surgical planning and 3-dimensional printed wafer achieved excellent maxillary positioning accuracies after orthognathic surgery.

Разработка программного обеспечения электропривода для группового управления в электромеханической системе

Background. To operate multi-coordinate electromechanical systems require control of electric drives coordinated in time and space along each of the axes, which is called coordinated control. Thus, various computing tools and mathematical algorithms are used. They establish the baseline of the software for microprocessor control systems. At the same time, the implementation of control algorithms is limited by the computing resources of the hardware parts of control systems, including the limitations of the tools of information transmission. To consider and eliminate these limitations and thus, to improve operation of the multi-coordinate electromechanical system, the aim of the article is to update control algorithms and balance distribution of computational resources of electric drives control systems. Materials and methods. Data are presented on the software development for coordinated control of several electric drives as a part of an electromechanical system that performs coordinated motion along its axes in time and space. To synchronize the control, the following technical solutions have been applied: description of the path of the high-level controller in the form of a sequence of reference points, buffering the coordinates when received by the electric drives and subsequent interpolation. Balanced distribution of resources between the high-level controller and local systems of electric drives is carried out considering the intensity of data exchange via the network interface. When calculating the reference points by the high-level controller, approximation of the paths by line segments at time intervals of variable duration is carried out to describe the generic path within the allowable mismatch. Results. The algorithm to synchronize the system time of the electric drives and the high-level controller has been implemented to synchronize the interpolation of paths. To implement this algorithm and transfer the coordinates of reference points to electric drives, special commands are used. They have different priority levels depending on the required speed of execution. In accordance with this algorithm, software has been developed as an element of the microprocessor control system of the electric drive. Conclusions. Application of various technical tools and computational algorithms that make it possible to allocate the computing resources of the control system and rationally use them contributes to efficiency improvement, in particular, the consistency and timeliness of electric drives control as a part of multi-axis electromechanical systems. The authors have proved the efficiency of the approach of coordinated control with the use of buffering coordinates of reference points followed by interpolation of the paths depending on the system time of each of the electric drives.

A fingerprint-based localization algorithm based on LSTM and data expansion method for sparse samples

The accuracy of WiFi fingerprint-based localization is related to the number of reference points, generally, to obtain better positioning accuracy, enough samples must be collected, which will inevitably lead to a huge sampling workload. Thus, it will be of great significance to design an algorithm using sparse samples to achieve positioning accuracy like that of dense samples. This paper proposes a WiFi fingerprint-based localization algorithm using Long Short-Term Memory Network (LSTM) with explainable feature and a sparse sample expansion algorithm (PGSE) based on Principal component analysis and Gaussian process regression for sparse samples. Specifically, in the case of limited number of collected reference points, principal component analysis is used to select the access point, and Gaussian process regression is used to model the reference point coordinates and the corresponding received signal strength values in the training sample set, to expand the signal data and construct a new fingerprint database. The effectiveness of the PGSE algorithm is verified by using the public dataset ’UJIIndoorLoc’. At the same time, the applicability of PGSE expansion algorithm to data with temporal information is verified in the fingerprint-based localization method. In addition, this paper also proposes a WiFi-RSSI indoor localization method based on Long Short-Term Memory Network. Lots of experiments are conducted in the actual scenes and the results are compared with several existing methods. The results indicate that the proposed method improves the precision of indoor localization on an average level compared to state-of-the-art methods.

Copernicus Sentinel–1 POD reprocessing campaign

Copernicus Sentinel–1 is a C-Band Synthetic Aperture Radar (SAR) satellite mission within the European Copernicus Programme. The two satellites Sentinel-1A and -1B were launched in April 2014 and 2016, respectively. The Copernicus POD (Precise Orbit Determination) Service is responsible for the determination of orbital and auxiliary products required by the Payload Data Ground Segment (PDGS). Precise orbits are determined based on the dual-frequency GPS (Global Positioning System) data delivered by dedicated geodetic-grade GPS receivers on-board the satellites. Several updates in the operational orbit determination were done during the years including an update of the GPS antenna reference point coordinates. The switch to GPS carrier phase ambiguity-fixing was a major improvement. A reprocessing of the entire mission span of both satellites became necessary to provide a consistent orbit time series for the mission based on state-of-the-art models and processing settings. Due to the lack of independent observation techniques, the Sentinel-1 orbit quality has been assessed by analysing processing metrics, orbit overlaps and orbit comparisons. For this purpose, members of the Copernicus POD Quality Working Group (QWG) provided reprocessed Sentinel-1 orbit time series based on their software packages and their orbit determination settings. A weighted average of all five delivered solutions - a combined orbit - serves as reference for the comparisons. The quality and reliability of this reference orbit depends among others on the number of available orbit solutions and whether a manoeuvre has been performed during the processed day or not. The mean orbit consistency between all orbit solutions is below 1 cm in 3D RMS for the entire mission time interval for both satellites. Only few days show inferior quality due to data gaps or orbit manoeuvres. Following this sophisticated validation process, the reprocessed Sentinel-1 orbits from the Copernicus POD Service have been made available to the user community.

Design method of a single degree-of-freedom planar linkage bionic mechanism based on continuous position constraints

Single degree-of-freedom (DOF) planar linkage mechanism has been widely used in bio-inspired robots because of its simple control. However, designing a single DOF mechanism to meet the complex motion law of creatures is difficult, and the multiple variables of six- or eight-bar mechanism further increase the design difficulty. A design method of single DOF planar linkage bionic mechanism is proposed in this paper. Through the continuous constraints on the position of all reference points with constraint descent method, the requirements of the bionic mechanism in shape, motion trajectory, and posture are met. As for the mechanism by which reference point coordinates cannot be expressed as the analytical solution of the driving angle, a single DOF mechanism is equivalent to a double DOF mechanism containing additional optimization variables, which further improves the design efficiency. For example, the design process of six- and eight-bar bionic mechanisms is given, confirming the feasibility of the method. Then, the effects of the constraint conditions on the design process are analyzed in detail. This study provides a reference for the design of bio-inspired robots.

AN ALTERNATIVE APPROACH TO CONTROL THE SHAPING OF PARTS WITH SPATIALLY COMPLEX SURFACES

In modern mechanical engineering, the number of parts with spatially complex surfaces is growing, the shape of which is determined analytically according to certain criteria. They are most widely used in the energy, aviation, tool industries (turbine blades, unicycles). With the current practice of processing such parts on CNC machines, when developing control programs, the analytically calculated shape of the surfaces is replaced by an approximate graphical model, which is used to calculate tool trajectories. This practice is due to the historically existing in the 1970-90s the capabilities of electronics and electrically driven devices. Despite the fundamentally new modern possibilities of computer control and electric drive devices, CNC machines retained the traditional initial principle of surface shaping using approximation and interpolation methods. At the same time, already at the stage of technological preparation of control programs, certain assumptions and losses in accuracy are assumed. The solution of this problem is relevant in connection with the current trend of increasing requirements for the accuracy of critical parts with spatially complex surfaces. The article proposes the principle of alternative control of shaping feeds when milling parts with spatially complex surfaces using the form of specifying the surface in an analytical form. The application of this principle excludes intermediate stages associated with the transformation of the analytical form of the task into a graphic one, the choice of coordinates of reference points and the interpolation of elementary sections. It is proposed, based on the proposed functional relationship between the geometric shape of a spatially complex surface and the established ratio of the components of the contour feed, based on the use of modern capabilities of computing devices and an electric drive, to provide a fundamentally new approach to shaping. The use of the proposed approach ensures complete automation of the preparation of control programs.

ГНСС-НАБЛЮДЕНИЯ НА ГЕОДИНАМИЧЕСКОМ ПОЛИГОНЕ НЕФТЕГАЗОВОГО МЕСТОРОЖДЕНИЯ: МЕТОДИКА, ОБРАБОТКА ДАННЫХ И ИХ АНАЛИЗ

To ensure geodynamic safety within the scope of their license areas, surveying services of the oil and gas complex create geodynamic polygons. When using GNSS technologies as a method of geody-namic monitoring, the question arises of choosing a coordination technology for a new point inserted into the reference geodetic network. According to a number of regulatory documents, in the develop-ment of satellite geodetic networks, only the "network" method should be used, while the "radiant" method is considered unacceptable. The use of the "network" method, as the main one in the organiza-tion of GNSS measurements at geodynamic polygons, leads to an increase in the observation time, which is obviously less in the "radiant" method. The authors, using its own Excel-program as a compu-ting tool, they show that the accuracy of the "radiant" and "network" methods is identical. Theoretical-ly, the points of the reference geodetic network of the geodetic construction under study are consid-ered as mathematical constants whose values are not subject to LS-optimization. As an experiment, GNSS measurements were used to bind the new Langepas point, which is part of the network of the regional geodynamic polygon of LLC LUKOIL-Western Siberia, to six reference points of the state geodetic network. Processing of observational materials was implemented using the algorithm of the synthesized version of the parametric method (SVPM) of LS-optimization of geospatial data, taking into account the errors of the coordinates of reference points. The coordinates of the defined point and their average quadratic errors turned out to be, of course, identical in both solutions: "radiant" and "network". This testifies in favor of the theoretically justified use of the "radiant” method, as less labo-rious in terms of the volume of field work. Additionally, within the framework of the same SVPS al-gorithm, the GNSS measurements on the specified object were treated as a "free" network. In the latter case, the average quadratic errors ofthecoordinates of the new inserted item sharply decreased. Pro-cessing of the same data on the synthesized variant of the correlate method with additional parameters (SVCMAP) again confirmed the results of the "radiation" method.

Gauss-Markov model with random parameters to adjust results of surveys of geodetic control networks

Abstract Alignment of an engineering object project in the field is always conducted at the points of the geodetic control network, the coordinates of which are determined on the basis of the results of its elements survey and with connection to the national spatial reference system. The points of the national spatial reference system determined on the basis of previous surveys have specified coordinates with adequate accuracy, which is included in their covariance matrix. The coordinates of the geodetic control network points are determined more accurately than the points of the national spatial reference system and this means that the results of surveys of the geodetic control network have to be adequately incorporated into the coordinates of the reference points. In order to perform this incorporation, it may be assumed that the coordinates of the reference points are random, that is, they have a covariance matrix, which should be used in the process of adjusting the results of the geodetic control network observation. This research paper presents the principles for the estimation of the Gauss-Markov model parameters applied in case of those geodetic control networks in which the coordinates of the reference points have random character. On the basis of the observation equations δ + AX = L for the geodetic control network and using the weighting matrix P and the matrix of conditional covariances (P −1 + AC X A T ) for the observation vector L, the parameter vector X is estimated in the form of the derived formula X ^ = ( C X − 1 + A T PA ) − 1 A T P ⋅ L {\bf{\hat X}} = {\left( {{\bf{C}}_X^{ - 1} + {{\bf{A}}^T}{\bf{PA}}} \right)^{ - 1}}{{\bf{A}}^T}{\bf{P}} \cdot {\bf{L}} . The verification of these estimation principles has been illustrated by the example of a fragment of a levelling geodetic control network consisting of three geodetic control points and two reference points of the national spatial reference system. The novel feature of the proposed solution is the application of covariance matrices of the reference point coordinates to adjust the results of the survey of geodetic control networks and to determine limit standard deviations for the estimated coordinates of geodetic control network points.

A generalized inertia representation for rigid multibody systems in terms of natural coordinates

The paper aims to investigate the appropriate Inertia Representation (IR) stemming from natural coordinates that is computationally efficient for rigid multibody systems with holonomic constraints. To this end, we develop the Generalized Inertia Representation (GIR) that results in a two-parameter family of formulations for the mass matrix. By properly selecting the parameters, the GIR includes the IRs of the Classical Natural Coordinates (CNC), the Natural Absolute Coordinates (NAC), and the Reference Point Coordinates featuring the Convected Base Vectors (RPC-CBV), etc. It is found that the parameters in the GIR influence the discretization error. Therefore, a parameter-preadjusting approach is proposed to improve the numerical accuracy of integrations. Comprehensive comparisons of numerical performances under the framework of the GIR are carried out using the variational integrator. We show that the GIR with preadjusted parameters achieves higher accuracy than other IRs. To achieve the same level of accuracy, the GIR requires fewer computations than the traditional IR of the CNC or the NAC. Therefore, the GIR with preadjusted parameters is preferred for long-time simulations of multibody systems, where the cost of preadjusting can be ignored.

Investigating persistent scatterer InSAR (PSInSAR) technique efficiency for landslides mapping: a case study in Artvin dam area, in Turkey

Monitoring and determining landslides in dam reservoirs is very crucial as it is one of the main factors of dam failures in the world. Coruh river basin is one of the most important river basin in the Northeast part of Turkey which accompanies five big dams. Although persistent scatterer InSAR (PSInSAR) method is a powerful remote sensing technique which can measure and monitor displacements of the Earth’s surface over time, its validation is a challenging issue because of the heterogeneous PS data. In this study, the efficiency of PSInSAR is investigated by proposing two different validation methods in order to see the consistency of the determined mean deformation velocities obtained with series of Sentinel-1A SAR-images. In the first method, 3D coordinates of reference points are projected to 1D displacement values in line of sight direction and then compared with the radar displacements of PS points. In the second method, new displacement values of PS points around reference points are identified from an interpolation map in order to be compared with the original displacements of reference points. In the end, it is showed that the displacements found by PSInSAR method are consistent with the reference points’ displacements measured in the study area. Finally, this work’s specific objectives are to present solutions to the challenging validation problem, to show the effectiveness of PSInSAR method and to describe the remaining challenges in PS analysis of landslide applications in dam areas.

POINT CLOUD TRANSFORMATION USING SENSOR CALIBRATION INFORMATION FOR MAP DATA ADJUSTMENT

Abstract. In order to operate autonomous vehicles and unmanned delivery vehicle, it is important to accurately acquire location of the device itself. However, since these devices are mainly operated in urban areas, there is a limit in obtaining location information based on GNSS. Therefore, it is necessary to utilize a method of calibrating its own location information by measuring the reference point provided by the existing high-precision map of the region. Point cloud based multi-dimensional high-precision maps are acquired in advance using high-performance LiDAR and GNSS devices for infrastructure such as roads, and provide a reference point for autonomous driving or map updating. Since such high-performance surveying equipment requires high cost, it is difficult to attach to autonomous vehicles or unmanned vehicle for commercialization. Therefore, autonomous vehicles or unmanned delivery vehicle are operated with relatively low performance LiDAR and GNSS, so it is often impossible to accurately measure the reference point, which directly leads to a decrease in the accuracy of the location information of the device. To compensate for this, this study proposes a point interpolation method to extract GCP information from sparse point cloud maps acquired with low performance LiDAR. The proposed method uses calibration parameters between point data and the image data acquired from the device. In general, images provide higher resolution than point clouds, even when using low-end cameras, so that the position of point coordinates relative to a reference point can be measured relatively accurately from the image and projection data of the point cloud. The data acquisition vehicle is an MMS vehicle that provides a panoramic image using four DSLRs and a point cloud with Velodyne VLP 16. The researchers first conducted a reference point survey on features such as road signs. The panorama image including the road sign was transformed into a bird eye’s view, and point projection was performed on the bird eye’s view image. The reference point coordinates, which were not acquired by the point cloud, were obtained from the shape of the road sign in the bird eye’s view image, and the accuracy was compared with the measured data.

A fingerprint-based coarse-to-fine algorithm for indoor positioning system using Bluetooth Low Energy

In this research, we propose a fingerprint-based fine-tuning algorithm to increase the accuracy of indoor positioning system using Bluetooth Low Energy fingerprint. In the fine-tuning step, Delta rule is used to update the coordinates of reference points based on the wireless environment represented in the training dataset. The combination of the coarse estimation and the proposed fine-tuning makes the coarse-to-fine algorithm. The algorithms used for coarse estimation are weighted sum and k-nearest neighbour, with three weight calculation algorithms that are compared in this experiment: Minkowski distance, k-means Gaussian mixture model, and autoencoder. Two subject rooms are used in order to measure the performance of the algorithms. The experiment showed that the fine-tuning algorithm improves the accuracy of the positioning throughout all combination of methods in both rooms, which shows its versatility. It reduces the mean positioning error by up to 11.3% and depends on what algorithm used in the weight calculation. Another benefit from the fine-tuning model is that it does not increase the complexity of the algorithm in the online phase. Overall, the best result is achieved by the combination of weighted sum and k-nearest neighbour with Minkowski distance weight calculation, together with the proposed fine-tuning. Its mean positioning error is 0.8740 m for Room 1 and 1.5385 for Room 2. The average computing time for a single online query is 0.4 ms for Room 1 and 0.7 ms for Room 2.