scholarly journals ERROR ANALYSIS FOR THE AIRBORNE DIRECT GEOREFERINCING TECHNIQUE

2016 ◽  
Vol XLI-B1 ◽  
pp. 1213-1219 ◽  
Author(s):  
Ahmed S. Elsharkawy ◽  
Ayman F. Habib
Keyword(s):  
Error Analysis ◽  
Calibration Procedure ◽  
Ground Control ◽  
Limiting Factor ◽  
Navigation Systems ◽  
Data Set ◽  
System Calibration ◽  
Inertial Component ◽  
Imaging Sensor ◽  
Orientation Parameters

Direct Georeferencing was shown to be an important alternative to standard indirect image orientation using classical or GPS-supported aerial triangulation. Since direct Georeferencing without ground control relies on an extrapolation process only, particular focus has to be laid on the overall system calibration procedure. The accuracy performance of integrated GPS/inertial systems for direct Georeferencing in airborne photogrammetric environments has been tested extensively in the last years. In this approach, the limiting factor is a correct overall system calibration including the GPS/inertial component as well as the imaging sensor itself. Therefore remaining errors in the system calibration will significantly decrease the quality of object point determination. <br><br> This research paper presents an error analysis for the airborne direct Georeferencing technique, where integrated GPS/IMU positioning and navigation systems are used, in conjunction with aerial cameras for airborne mapping compared with GPS/INS supported AT through the implementation of certain amount of error on the EOP and Boresight parameters and study the effect of these errors on the final ground coordinates. <br><br> The data set is a block of images consists of 32 images distributed over six flight lines, the interior orientation parameters, IOP, are known through careful camera calibration procedure, also 37 ground control points are known through terrestrial surveying procedure. The exact location of camera station at time of exposure, exterior orientation parameters, EOP, is known through GPS/INS integration process. The preliminary results show that firstly, the DG and GPS-supported AT have similar accuracy and comparing with the conventional aerial photography method, the two technologies reduces the dependence on ground control (used only for quality control purposes). Secondly, In the DG Correcting overall system calibration including the GPS/inertial component as well as the imaging sensor itself is the limiting factor to achieve good object space.

Simple Index to Assess the Calibration Quality of Safety Performance Functions Based on Multiple Goodness-of-Fit Metrics

2021 ◽  
pp. 036119812110088
Author(s):  
Raul E. Avelar ◽  
Karen Dixon ◽  
Boniphace Kutela ◽  
Sam Klump ◽  
Beth Wemple ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Synthetic Data ◽  
Calibration Procedure ◽  
Safety Performance ◽  
Absolute Deviation ◽  
Data Set ◽  
Safety Database ◽  
Simple Index ◽  
Safety Performance Functions

The calibration of safety performance functions (SPFs) is a mechanism included in the Highway Safety Manual (HSM) to adjust SPFs in the HSM for use in intended jurisdictions. Critically, the quality of the calibration procedure must be assessed before using the calibrated SPFs. Multiple resources to aid practitioners in calibrating SPFs have been developed in the years following the publication of the HSM 1st edition. Similarly, the literature suggests multiple ways to assess the goodness-of-fit (GOF) of a calibrated SPF to a data set from a given jurisdiction. This paper uses the calibration results of multiple intersection SPFs to a large Mississippi safety database to examine the relations between multiple GOF metrics. The goal is to develop a sensible single index that leverages the joint information from multiple GOF metrics to assess overall quality of calibration. A factor analysis applied to the calibration results revealed three underlying factors explaining 76% of the variability in the data. From these results, the authors developed an index and performed a sensitivity analysis. The key metrics were found to be, in descending order: the deviation of the cumulative residual (CURE) plot from the 95% confidence area, the mean absolute deviation, the modified R-squared, and the value of the calibration factor. This paper also presents comparisons between the index and alternative scoring strategies, as well as an effort to verify the results using synthetic data. The developed index is recommended to comprehensively assess the quality of the calibrated intersection SPFs.

scholarly journals Registration Error Analysis for Augmented Reality

1997 ◽  
Vol 6 (4) ◽  
pp. 413-432 ◽  
Author(s):  
Richard L. Holloway
Keyword(s):  
Augmented Reality ◽  
Error Analysis ◽  
Optical Distortion ◽  
Calibration Error ◽  
Head Tracking ◽  
System Delay ◽  
System Calibration ◽  
The Real ◽  
Registration Error ◽  
Real Environment

Augmented reality (AR) systems typically use see-through head-mounted displays (STHMDs) to superimpose images of computer-generated objects onto the user's view of the real environment in order to augment it with additional information. The main failing of current AR systems is that the virtual objects displayed in the STHMD appear in the wrong position relative to the real environment. This registration error has many causes: system delay, tracker error, calibration error, optical distortion, and misalignment of the model, to name only a few. Although some work has been done in the area of system calibration and error correction, very little work has been done on characterizing the nature and sensitivity of the errors that cause misregistration in AR systems. This paper presents the main results of an end-to-end error analysis of an optical STHMD-based tool for surgery planning. The analysis was done with a mathematical model of the system and the main results were checked by taking measurements on a real system under controlled circumstances. The model makes it possible to analyze the sensitivity of the system-registration error to errors in each part of the system. The major results of the analysis are: (1) Even for moderate head velocities, system delay causes more registration error than all other sources combined; (2) eye tracking is probably not necessary; (3) tracker error is a significant problem both in head tracking and in system calibration; (4) the World (or reference) coordinate system adds error and should be omitted when possible; (5) computational correction of optical distortion may introduce more delay-induced registration error than the distortion error it corrects, and (6) there are many small error sources that will make submillimeter registration almost impossible in an optical STHMD system without feedback. Although this model was developed for optical STHMDs for surgical planning, many of the results apply to other HMDs as well.

scholarly journals The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?

2021 ◽  
Vol 4 ◽  
Author(s):  
Stefano Markidis
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
High Performance ◽  
Critical Role ◽  
Low Frequency ◽  
Accurate Solution ◽  
Limiting Factor ◽  
Data Set ◽  
Linear Solvers ◽  
Computational Performance

Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged as a new essential tool to solve various challenging problems, including computing linear systems arising from PDEs, a task for which several traditional methods exist. In this work, we focus first on evaluating the potential of PINNs as linear solvers in the case of the Poisson equation, an omnipresent equation in scientific computing. We characterize PINN linear solvers in terms of accuracy and performance under different network configurations (depth, activation functions, input data set distribution). We highlight the critical role of transfer learning. Our results show that low-frequency components of the solution converge quickly as an effect of the F-principle. In contrast, an accurate solution of the high frequencies requires an exceedingly long time. To address this limitation, we propose integrating PINNs into traditional linear solvers. We show that this integration leads to the development of new solvers whose performance is on par with other high-performance solvers, such as PETSc conjugate gradient linear solvers, in terms of performance and accuracy. Overall, while the accuracy and computational performance are still a limiting factor for the direct use of PINN linear solvers, hybrid strategies combining old traditional linear solver approaches with new emerging deep-learning techniques are among the most promising methods for developing a new class of linear solvers.

Design, modeling, and simulation of an INS system using an asymmetric structure of six accelerometers and its error analysis in the ECEF frame

2016 ◽  
Vol 231 (13) ◽  
pp. 2345-2361 ◽  
Author(s):  
Vahid Ghasemzadeh ◽  
Mohammad M Arefi
Keyword(s):  
Error Analysis ◽  
Lower Cost ◽  
Inertial Navigation ◽  
Asymmetric Structure ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Symmetric Structure ◽  
Angular Velocities ◽  
Dynamic Relations ◽  
Short Time

The inertial navigation system is one of the most important and common methods of navigation. In this system, accelerometers and gyroscopes are used to measure linear accelerations and angular velocities, respectively. Accelerometers have simpler manufacture techniques, lower cost, and smaller volume and weight in comparison with gyroscopes. Therefore, in some application of navigation systems, non-gyro inertial navigation systems based on accelerometers are used. In this paper, an asymmetric structure of six accelerometers is proposed. Then dynamic relations of this structure are extracted. This structure and its relations can determine linear accelerations and angular velocities, completely. Moreover, the algorithm of inertial navigation in earth centered earth fixed (ECEF) frame is suggested. Error analysis as of the most important issues in inertial navigation is discussed. Thus, bias, misalignment, sensitivity, and noise of accelerometers are modeled appropriately. In addition, a symmetric structure of accelerometers is proposed and its equations are derived. Finally, the designed system, error model of accelerometers, and algorithm of inertial navigation in ECEF frame are simulated. The results of simulation show that the designed system has suitable accuracy and applications for short time navigation. Furthermore, results confirm that the proposed asymmetric structure requires less accelerometer in comparison with symmetric structure.

Convenient Calibration Procedure for Structured Light Projection System

2013 ◽  
Vol 662 ◽  
pp. 777-780
Author(s):  
Wen Guo Li ◽  
Shao Jun Duan
Keyword(s):  
Relative Position ◽  
Structured Light ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Shape Measurement ◽  
Projection System ◽  
System Calibration ◽  
3D Shape ◽  
3D Shape Measurement ◽  
Projector Calibration

We present a convenient calibration method for structured light projection system. The proposed clibration approach can realize 3D shape measurement without projector calibration, without system calibration, without precise linear z stage to be used, the relative position between camera and projector can be arbitrary, and the only involved device is a plane board. Experiment results validated that the accuracy of the proposed approach.

A Bayesian approach to modeling 2D gravity data using polygons

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. G1-G21 ◽  
Author(s):  
William J. Titus ◽  
Sarah J. Titus ◽  
Joshua R. Davis
Keyword(s):  
Gravity Data ◽  
Synthetic Data ◽  
Gravity Inversion ◽  
Limiting Factor ◽  
Data Sets ◽  
Data Set ◽  
Local Optima ◽  
Occupancy Probability ◽  
Compute Model ◽  
Parameter Values

We apply a Bayesian Markov chain Monte Carlo formalism to the gravity inversion of a single localized 2D subsurface object. The object is modeled as a polygon described by five parameters: the number of vertices, a density contrast, a shape-limiting factor, and the width and depth of an encompassing container. We first constrain these parameters with an interactive forward model and explicit geologic information. Then, we generate an approximate probability distribution of polygons for a given set of parameter values. From these, we determine statistical distributions such as the variance between the observed and model fields, the area, the center of area, and the occupancy probability (the probability that a spatial point lies within the subsurface object). We introduce replica exchange to mitigate trapping in local optima and to compute model probabilities and their uncertainties. We apply our techniques to synthetic data sets and a natural data set collected across the Rio Grande Gorge Bridge in New Mexico. On the basis of our examples, we find that the occupancy probability is useful in visualizing the results, giving a “hazy” cross section of the object. We also find that the role of the container is important in making predictions about the subsurface object.

scholarly journals Ocean Backscatter Profiling Using High-Spectral-Resolution Lidar and a Perturbation Retrieval

2018 ◽  
Vol 10 (12) ◽  
pp. 2003 ◽  
Author(s):  
James Churnside ◽  
Johnathan Hair ◽  
Chris Hostetler ◽  
Amy Scarino
Keyword(s):  
Attenuation Coefficient ◽  
Spectral Resolution ◽  
Calibration Procedure ◽  
High Spectral Resolution ◽  
Scattering Parameters ◽  
Scattering Parameter ◽  
Data Set ◽  
Coefficient Of Variability ◽  
High Spectral Resolution Lidar

Ocean lidar attenuation and scattering parameters were derived from a high-spectral-resolution lidar (HSRL) using two different retrieval techniques. The first used the standard HSRL retrieval, and the second used only the total backscatter channel and a perturbation retrieval (PR). The motivation is to evaluate differences between the two techniques that would affect the decision of whether to use a simple backscatter lidar or a more complex HSRL in future applications. For the data set investigated, the attenuation coefficient from the PR was an average of 11% lower than that from the HSRL. The PR estimate of the scattering parameter decreased with depth relative to the HSRL estimate, although the overall bias was zero as a result of the calibration procedure. Near the surface, the coefficient of variability in both estimates of attenuation and in HSRL estimates of scattering were around 5%, but that in the PR estimate of scattering was over 10%. At greater depths, the variability increases for all of the profile parameters. The correlation between the two estimates of attenuation coefficient was 0.7. The correlation between scattering parameters was > 0.8 near the surface, but decreased to 0.4 at a depth of around 20 m. Overall, the PR performed better relative to the HSRL in offshore waters than in nearshore waters.

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