Coordinate Domain Research Articles

Possible impact of construction activities around a permanent GNSS station – A time series analysis

Abstract In this article, we address the potential effects of construction activities around a permanent Global Navigation Satellite System (GNSS) station. The study is based on a consistent time series of GNSS observations collected over a span of almost 13 years and comprises an analysis in both observation and coordinate domains. The analysis in the observation domain revealed a significant increase of the code multipath for the C1C signal of GPS and GLONASS. In terms of standard deviations the values increased by 37 and 31%, respectively. No significant increase was observed for other signals. Interestingly, the analysis showed that the Galileo E5 AltBOC signal outperformed the other signals in distinguishing direct from indirect signals. In the coordinate domain, the relative GNSS solution results demonstrated an increase in root mean square error for the eastern component during the same period. Noteworthy, the observed increase in both domains coincided with the period of the highest level of construction activity around the GNSS station. These findings suggest that the construction activity near the station impacted the quality of GNSS observations and that the Galileo E5 AltBOC signal was better at compensating for local changes than other signals.

The Modified Ambiguity Function Approach with regularization for instantaneous precise GNSS positioning

Abstract The Modified Ambiguity Function Approach (MAFA) implicitly conducts the search procedure of carrier phase GNSS integer ambiguity resolution (IAR) in the coordinate domain using the integer least squares (ILS) principle, i.e. MAFA-ILS. One of the still open scientific problems is an accurate definition of the search region, especially in the context of instantaneous IAR. In doing so, the float solution results, which encompass float position (FP) and its variance-covariance (VC) matrix, must be improved as these are necessary for defining the search region. For this reason, the ambiguity parameters are separately regularized, and then the baseline parameters are conditioned on regularized float ambiguities. The conditional-regularized estimation is thus designed, obtaining the regularized FP (RFP) and its VC-matrix. This solution is promising because its accuracy is enhanced in the sense of mean squared error (MSE) thanks to the improved precision at the cost of regularized bias. The optimal regularization parameter (RP) values obtained for ambiguity parameters balance the contributions of improved precision and bias in the regularized float baseline solution’s MSE. Therefore, the regularized search region is defined accurately in the coordinate domain to contain such approximate coordinates that more frequently give the correct ILS solution. It also contains fewer MAFA-ILS candidates, improving the search procedure’s numerical efficiency. The regularized ILS estimator performs well with the presence of bias, increasing the probability of correct IAR in the coordinate domain.

51‐2: Invited Paper: Foveated Image Transmission with Anti‐Aliasing Image Reconstruction

This paper introduces an anti‐aliasing image reconstruction method in the optical coordinate domain for point‐to‐point transmission in AR/VR headset displays, employing variable downsampling ratios across different image areas to reduce transmission bandwidth and corresponding upscaling ratios at the receiver. Filter parameters for anti‐aliasing calculations at each pixel position are determined based on optical coordinates distorted by the lens, enhancing detail in areas with significant image deformation. Image quality is evaluated using MSSSIM and supported by experimental evidence.

GNSS Carrier-Phase Multipath Modeling and Correction: A Review and Prospect of Data Processing Methods

A multipath error is one of the main sources of GNSS positioning errors. It cannot be eliminated by forming double-difference and other methods, and it has become an issue in GNSS positioning error processing, because it is mainly related to the surrounding environment of the station. To address multipath errors, three main mitigation strategies are employed: site selection, hardware enhancements, and data processing. Among these, data processing methods have been a focal point of research due to their cost-effectiveness, impressive performance, and widespread applicability. This paper focuses on the review of data processing mitigation methods for GNSS carrier-phase multipath errors. The paper begins by elucidating the origins and mitigation strategies of multipath errors. Subsequently, it reviews the current research status pertaining to data processing methods using stochastic and functional models to counter multipath errors. The paper also provides an overview of filtering techniques for extracting multipath error models from coordinate sequences or observations. Additionally, it introduces the evolution and algorithmic workflow of sidereal filtering (SF) and multipath hemispherical mapping (MHM), from both coordinate and observation domain perspectives. Furthermore, the paper emphasizes the practical significance and research relevance of multipath error processing. It concludes by delineating future research directions in the realm of multipath error mitigation.

中国社交媒体环境下“宝妈创业者”的职业叙述：自我、孩子与生意

In the past decades, women-owned businesses have increased significantly. A large portion of these entrepreneurs are mothers who combine entrepreneurship with raising their children and are also known as ‘mompreneurs’. Researchers have highlighted the impact of changes at critical life stages on mothers’ career decisions, and noted that the unique way that entrepreneurial mothers coordinate roles, relationships, and domain involvement has an important influence on their career patterns. Despite a growing interest in women’s career-life development and entrepreneurship, relatively few researches have been conducted on the entrepreneurial career of self-employed mothers with dependent children. This research seeks to understand how mompreneurs perceive the relationship between self, business, and children. Adopting a career narrative perspective, this study applies a qualitative interview research design, the data were collected through open-ended, semi-structured interviews by face to face or Skype, supplemented by questionnaire. The twelve mothers’ interviews were a small sample of the most ordinary mompreneurs in China, they were recruited by purposive sampling and snowball sampling method. The study proposes ‘six entrepreneurial career types’ to explain why mother mothers’ transit into entrepreneurship, and is dedicated to providing theoretical and practical references for researchers and practitioners engaged in female entrepreneurship and career counseling.

BDS Dual-Frequency Carrier Phase Multipath Hemispherical Map Model and Its Application in Real-Time Deformation Monitoring.

The BDS multipath delay error is highly related to the surrounding monitoring environment, which cannot be eliminated or mitigated by applying the double difference observation model. In the actual monitoring environment, due to the complexity of the BDS constellation, it is difficult for existing algorithms to consider GEO, IGSO, MEO and other different orbital types of satellites for real-time and efficient multipath error reduction. Therefore, we propose a novel BDS dual-frequency multipath error reduction method for real deformation monitoring for BDS considering various satellite orbit types. This method extracts the single error residual of each satellite based on the assumption of "zero mean" and divides the appropriate grid density of GEO and IGSO/MEO, respectively, to construct a dual-frequency multipath hemispherical map model suitable for BDS satellites with different orbital types. This method can realize the multipath error elimination of the observed values of different orbits and different frequencies. The results of simulation experiments and real deformation monitoring data demonstrate that this method can effectively eliminate low-frequency multipath delay errors in the observation domain and coordinate domain. After multipath correction, the precision of the horizontal coordinates and height coordinates are 1.7 mm and 4.6 mm. The precision of the horizontal coordinate and height coordinate is increased by 50% and 60%, respectively. The fixed rate of ambiguity increased by 5-7%.

The enhanced search procedure in a coordinate domain for precise satellite positioning

Recently, there has been an increase in the availability of GNSS satellites for observation, which poses new challenges in the computational process of precise satellite positioning. Ambiguity resolution is a crucial step in achieving accurate relative positioning. In this regard, an improved version of a searching procedure in a three-dimensional coordinate domain has been proposed and tested. The method starts with a float solution, similar to classic methods like the LAMBDA. However, the subsequent step, the search procedure, is conducted in the coordinate space instead of the ambiguity space. This shift to a three-dimensional coordinate space leads to reduced computation time. A computational experiment was performed to validate the proposed method, which demonstrated a significant reduction in processing time. The advantages of this method are particularly prominent when dealing with a large number of satellites.

Airfoil GAN: encoding and synthesizing airfoils for aerodynamic shape optimization

Abstract The current design of aerodynamic shapes, like airfoils, involves computationally intensive simulations to explore the possible design space. Usually, such design relies on the prior definition of design parameters and places restrictions on synthesizing novel shapes. In this work, we propose a data-driven shape encoding and generating method, which automatically learns representations from existing airfoils and uses the learned representations to generate new airfoils. The representations are then used in the optimization of synthesized airfoil shapes based on their aerodynamic performance. Our model is built upon VAEGAN, a neural network that combines Variational Autoencoder with Generative Adversarial Network and is trained by the gradient-based technique. Our model can (1) encode the existing airfoil into a latent vector and reconstruct the airfoil from that, (2) generate novel airfoils by randomly sampling the latent vectors and mapping the vectors to the airfoil coordinate domain, and (3) synthesize airfoils with desired aerodynamic properties by optimizing learned features via a genetic algorithm. Our experiments show that the learned features encode shape information thoroughly and comprehensively without predefined design parameters. By interpolating/extrapolating feature vectors or sampling from Gaussian noises, the model can automatically synthesize novel airfoil shapes, some of which possess competitive or even better aerodynamic properties as compared to airfoils used for model training purposes. By optimizing shapes on the learned latent domain via a genetic algorithm, synthesized airfoils can evolve to target aerodynamic properties. This demonstrates an efficient learning-based airfoil design framework that encodes and optimizes the airfoil on the latent domain and synthesizes promising airfoil candidates for required aerodynamic performance.

Multi-layer security based multiple image encryption technique

This paper designs a novel multiple image encryption technique utilizing affine Hill cipher (AHC), reality-preserving two-dimensional discrete fractional Hartley transform (RP2DFrHT) and generalized two-dimensional (2D) Arnold map (AM). In our technique, three indexed images are obtained from three color images. Afterwards, AHC performs a strong degree of confusion and diffusion operations and RP2DFrHT provides real domain output image. Lastly, 2D AM dislocates the image pixel position. After the encryption process, single-channel real-valued encrypted image is obtained which gives convenience in the display, storage and transmission of an image over an unsecured network. The proposed technique is multi-layer secured in the time, frequency and co-ordinate domains. Moreover, the secret keys, arrangements and positions of used parameters all are imperative for the correct decryption process of our technique. Simulation results, security analysis, statistical analysis and comparison analysis ensure that the proposed technique has an excellent encryption effect, sufficient security and robustness.

Reduction as an improvement of a precise satellite positioning based on an ambiguity function

Abstract It is well-known that the solution domain has a discrete character in precise satellite positioning because of the integer nature of ambiguities. Therefore, in addition to the classic least squares estimation, the search procedure has to be employed in the computation process to obtain the so-called ‘fixed solution.’ The article’s subject is to improve the search procedure conducted in the coordinate domain. The reduction process is to transform the original math model into an equivalent one in the sense of obtaining the same solution. The reduction aims to increase the efficiency of searching for some parameters, i. e., integer ambiguities. The article presents the concept of employing the reduction procedure to the computation process of precise positioning based on the ambiguity function. The transformation matrix for the reduction is based on the well-known integer decorrelation procedure. Numerical experiment results display a positive impact of the reduction process on the search procedure efficiency. This positive impact is manifested by a dramatic decrease in the number of candidates needed to test all admissible solutions inside the search region. The percentage decrease in that magnitude is at least 50 % for all session lengths and achieves a maximum value of over 75 % for the 10-minute session. Computational time decreases by over 40 % while short sessions are processed. There is no improvement for sessions longer than 15 minutes, but, as explained in the paper, there is no need to improve that magnitude in such cases.

Cardiac Segmentation Method Based on Domain Knowledge.

Echocardiography plays an important role in the clinical diagnosis of cardiovascular diseases. Cardiac function assessment by echocardiography is a crucial process in daily cardiology. However, cardiac segmentation in echocardiography is a challenging task due to shadows and speckle noise. The traditional manual segmentation method is a time-consuming process and limited by inter-observer variability. In this paper, we present a fast and accurate echocardiographic automatic segmentation framework based on Convolutional neural networks (CNN). We propose FAUet, a segmentation method serially integrated U-Net with coordinate attention mechanism and domain feature loss from VGG19 pre-trained on the ImageNet dataset. The coordinate attention mechanism can capture long-range dependencies along one spatial direction and meanwhile preserve precise positional information along the other spatial direction. And the domain feature loss is more concerned with the topology of cardiac structures by exploiting their higher-level features. In this research, we use a two-dimensional echocardiogram (2DE) of 88 patients from two devices, Philips Epiq 7C and Mindray Resona 7T, to segment the left ventricle (LV), interventricular septal (IVS), and posterior left ventricular wall (PLVW). We also draw the gradient weighted class activation mapping (Grad-CAM) to improve the interpretability of the segmentation results. Compared with the traditional U-Net, the proposed segmentation method shows better performance. The mean Dice Score Coefficient (Dice) of LV, IVS, and PLVW of FAUet can achieve 0.932, 0.848, and 0.868, and the average Dice of the three objects can achieve 0.883. Statistical analysis showed that there is no significant difference between the segmentation results of the two devices. The proposed method can realize fast and accurate segmentation of 2DE with a low time cost. Combining coordinate attention module and feature loss with the original U-Net framework can significantly increase the performance of the algorithm.

On numerical approximations to fluid–structure interactions involving compressible fluids

In this paper we introduce a numerical scheme for fluid–structure interaction problems in two or three space dimensions. A flexible elastic plate is interacting with a viscous, compressible barotropic fluid. Hence the physical domain of definition (the domain of Eulerian coordinates) is changing in time. We introduce a fully discrete scheme that is stable, satisfies geometric conservation, mass conservation and the positivity of the density. We also prove that the scheme is consistent with the definition of continuous weak solutions.

Consistency Analysis of the GNSS Antenna Phase Center Correction Models

For the same antenna type, numerical differences among the phase center correction (PCC) models released by different institutes can reach several millimeters, which is far beyond the nominal calibration accuracy. This contribution introduces a new method to evaluate the consistency of these PCC models. We first investigated the coupling of phase center offset (PCO) and phase center variation (PCV) through simulation experiments, and the results show that the calibrated PCO values under different strategies may result in large differences, and so do PCV values due to strong coupling with PCO. This is further confirmed by field calibration experiments. Moreover, a new datum parameter is introduced to equivalently transform the PCC models to assess the consistency of PCC models of the same antenna type calibrated under different strategies or by different facilities. It is also essential to perform consistency analysis of PCC models in the coordinate domain. We further investigated these PCC models through a simulated positioning experiment. The results show that millimeter-level consistency of PCC models will lead to the same level of positioning precision in the coordinate domain. Moreover, as a comparison, both baseline positioning and PPP were performed with an antenna-type JAV_RINGANT_G3T NONE based on real observations. Multiday results showed that the average RMS of the positioning differences between PCC models from robot and anechoic chamber calibration is less than 1 mm for the baseline solution and 4 mm for the PPP solution, although the PCC model differences can reach 6 mm in L1 and 4 mm in L2, respectively. Finally, we also investigated the distribution of position biases without PCC or with inaccurate PCC. Considering the actual GPS constellation, we found that position biases have a strong correlation with latitude, if PCV values fluctuate greatly with the users’ elevation angle.

Nearly Reversible ECG Steganography based on Polar Coordinate System with Digital Replacement Technique

In this paper, we present a nearly reversible data hiding for electrocardiogram (ECG) hosts. Based on the polar coordinate system domain, medical diagnosis and personal data can be embedded in an ECG signal by the simple digital replacement technique. Simulations revealed that the restored ECG with near lossless quality can be obtained by the proposed method at receiver site. In addition, the perceived quality of the marked ECG is very good with a high payload size. Moreover, the resultant signal-to-noise ratio (SNR), peak SNR, and payload of the proposed method outperforms those of existing techniques. Since the computation cost is low, the proposed method can be used in portable biometrics or ECG measuring instruments.

MULTIPLE RGB IMAGE ENCRYPTION ALGORITHM WITH MULTILAYERS BY AFFINE HILL CIPHER WITH FRDCT AND ARNOLD TRANSFORM

In this paper, we aim to investigate the security of multiple images based on affine hill cipher (AHC), fractional discrete cosine transform (FrDCT) and Arnold transform (AT). Three original [Formula: see text] images are encoded as a single [Formula: see text] image by first converting three [Formula: see text] images into three indexed images by extracting their color maps. These three indexed image are treated as [Formula: see text], [Formula: see text] and [Formula: see text] channel of a single [Formula: see text] image. Each channel is first encrypted using cryptographic encryption scheme AHC in time domain. The partially encoded image is transformed to frequency domain using FrDCT. In frequency domain, the partially encoded image is scrambled with the help of AT. The proposed scheme assures security in time domain, frequency domain as well as in coordinate domain. The original images can be recovered correctly by using proper arrangements of secret keys. The storage and transmission of the encrypted image is easy due to single encrypted image. The robustness of the proposed approach is proved by conducting computer simulations on standard examples.

Lensless Reflection Imaging of Obliquely Illuminated Objects I: Choosing a Domain for Phase Retrieval and Ptychography

Ptychography is a lensless imaging technology that is validated from hard X-rays to terahertz spectral range. It is most attractive for extreme ultraviolet (EUV) and X-rays as optical elements are expensive and often not available. Typically, the set up involves coherently illuminated object that directs the scattered radiation normally to detector which is parallel to the object plane. Computer processing of diffraction patterns obtained when scanning the object gives the image, more precisely, the distribution of intensity and phase on its surface. However, this scheme is inefficient for EUV and X-rays due to poor reflectivity and low penetration in all materials. Reflection mode ptychography solves the problem if illumination angles do not exceed the critical angle of object material. Changing the geometry of experiment changes physical and mathematical model of image formation. Including: diffraction integral describing beam propagation from object to detector, inverse problem, optimization of object illumination angle, position and orientation of detector, choosing size and grid of coordinate and frequency computer domains. This paper considers the wavefield scattered to detector by obliquely illuminated object and determines a domain for processing of obtained scans. Solution of inverse problem with phase retrieval and resulting numerical images will be presented in the next paper.

Multi-layer color image encryption using random matrix affine cipher, RP2DFrHT and 2D Arnold map

Confidentiality, integrity, authenticity, non-repudiation and storing and transmitting images over the unsecured channel has become a challenging task nowadays. In this scenario, a robust image encryption technique over open network has grasped a great deal of attention. In this paper to meet this challenge, we have established a new multi-layer robust color image encryption using random matrix affine cipher (RMAC), reality preserving two dimensional discrete fractional Hartley transform (RP2DFrHT) and two dimensional Arnold map. The first stage of encryption is designed through RMAC. RMAC provides security in co-ordinate domain as well as in geometrical domain. So if a hacker has knowledge about all the pixels of an image, but has no information about the mechanism of co-ordinate domain he/she cannot steal any information. The second stage of encryption is obtained incorporating the concept of RP2DFrHT. The reality preserving transform eliminates the complex-valued coefficients and provides the real-valued coefficients of encrypted image. The real-valuedness of data provides convenient platform for display, storage and transmission in digital domain. The third stage of encryption is done using 2D Arnold map, which not only enhances the security but also enlarges key space. Therefore, the proposed technique provides security in geometrical, co-ordinate, frequency and time domains simultaneously. The security of our proposed technique depends upon the secret keys as well as their correct arrangements. Simulation analysis provides the complete visual results of all stages of encrypted and decrypted images. Sensitivity analysis validates that our proposed technique is highly sensitive towards its secret keys and their arrangements. Statistical analysis such as histogram analysis, MSE, PSNR, correlation coefficient, entropy analysis and resistivity of classical attacks validates the effectiveness and feasibility of our proposed work. Moreover, comparison analysis testifies that our proposed technique functions significantly well as compared to existing similar techniques.

A search step optimization in an ambiguity function-based GNSS precise positioning

The search procedure, as a part of the Modified Ambiguity Function Approach (MAFA), is conducted in the coordinate space. The main advantage of searching for a fixed solution in the coordinate domain, instead of in the ambiguity domain, is the constant search space dimension, which amounts to three. In contrast, an ambiguity space dimension can presently achieve over twenty when the positioning is based on multi-system data. Thus, in the MAFA method, the computational complexity is independent of the number of satellites. We propose a new method of estimating the length of the search step. In this method, the actual satellite configuration determines the size of the search step. Therefore, the data-driven search step is always optimal, regardless of the current satellite configuration. The mathematical model of the new approach is provided together with a detailed algorithm. The numerical experiment follows the description of the search procedure.

Multi-frequency multi-GNSS receiver antenna calibration at IfE: Concept - calibration results - validation

Multi-frequency and multi-constellation GNSS have the potential to boost the overall performance of GNSS-based positioning, navigation and timing. This has an impact on the realisation of global reference frames, geophysical monitoring applications as well as enabling new applications. To this end, all error sources should be adequately corrected for. However, currently multi-frequency multi-GNSS receiver antenna calibration values are still missing. In this paper, the newly developed multi-frequency multi-GNSS calibration process at Institut für Erdmessung (IfE), Leibniz University Hannover, is presented. The basic concept and the assumptions for the antenna calibration are described. Resulting phase centre corrections (PCC) for GPS and Galileo for typical antennas are presented. We show that the repeatability of the estimated patterns are almost better than 2 mm in terms of maximum deviation and that the used tracking strategies by the receivers have marginal impact on the patterns, at maximum 1.2 mm for the studied receiver-antenna combinations. Furthermore, applying phase centre corrections for multi-frequency multi-GNSS carrier phase observations reduces significantly (up to 37%) the antenna related biases as validated on short baselines. Moreover, a validation in the coordinate domain shows that with IfE PCC a short baseline can be computed with high accuracy: the topocentric coordinate differences to the known baseline are in most cases smaller than 1 mm for the horizontal components and smaller than 2.2 mm in vertical.

GNSS Multipath Errors Mitigation Algorithm Based on Observation Domain for Landslide Deformation Monitoring

The Global Navigation Satellite System (GNSS) real-time kinematic (RTK) technology is widely used for landslide deformation monitoring due to its precision and simplicity of its algorithm. However, GNSS signals are susceptible to multipath effects under complex circumstances such as terrain and surrounding vegetation. Reducing the impact of multipath errors and improving the RTK positioning accuracy is vital in ensuring accurate landslide monitoring in mountainous regions. The traditional method based on sidereal filtering in the coordinate domain only considers comprehensive multipath errors of all satellites, and the calculated time shift of coordinate sequence is not very accurate. In this paper, a sidereal filtering algorithm based on the double-difference residual in the GNSS observation domain is used for mitigating the multipath errors of landslide deformation monitoring in mountainous regions. First, we calculate the double-difference residuals of the observation in the previous cycle. Next, the empirical mode decomposition (EMD) filtering is used for denoising double-difference residual sequences. Based on the calculated period of the respective satellite, we use the residuals to correct the double-difference observation equation. Subsequently, we obtain the clean double-difference observations after mitigating multipath errors. Finally, the baseline coordinates of all monitoring stations can be calculated. The experimental results show that this method effectively improves the accuracy of GNSS landslide deformation monitoring in mountainous regions and the improved effect exceeds the traditional sidereal filtering algorithm in the coordinate domain.