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

The multipath effect is a crucial error source caused by the environment around the station and cannot be eliminated or mitigated by differential algorithms. Theoretically, the maximum value for the carrier phase is a quarter the wavelength, i.e., about 4.8 cm for the GPS L1 signal. Considering the increasing demands of high-precision applications, the multipath error has become a major factor affecting the accuracy and reliability of GPS millimeter-level data processing. This paper proposes a multi-point hemispherical grid model (MHGM) to mitigate the multipath effect. In this method, the hemisphere centered on each station is divided into a grid, and the multipath error at the station is estimated based on the parameterization of the grid points. The double-differenced (DD) observed-minus-calculated (OMC) values on some previous days are treated as the observation values to model the present multipath error. Contrary to the present methods which rely much on the platform of data collection and processing, MHGM can be potentially applied to GPS data processing with the existing hardware and software. Experiments in high-multipath and low-multipath environments are designed by mounting a baffle or not. The experimental results show that MHGM is effective in mitigating the multipath effect. When using data from the previous day, an average improvement of about 63.3% in the RMS of DD OMC can be made compared with that without correction, and this is basically consistent with the sidereal filtering (SF) method which is 63.0%. Furthermore, the effectiveness of the above two methods is better than that of the empirical site model (ESM). The kinematic positioning results are also basically consistent with the statistical results of the RMS values of DD OMC. Historical data from more than one day can more explicitly and effectively model the MHGM. Furthermore, compared with the SF method, the MHGM can be used not only to mitigate the multipath error, but also to orientate the sources of the multipath error around the station, and give guidance in the physical elimination of these sources.

In GNSS real-time high-precision monitoring, the multipath spatial correlation is weak, it is difficult to eliminate the multipath error by double difference, and the traditional method based on the sidereal filtering in the coordinate domain to mitigate multipath error of MEO satellite will no longer be applicable. Aiming at the above problem, this paper storage single difference observation residuals after ambiguity resolved in real-time baseline resolution, where storage residual information for 1d in GPS, BDS GEO, IGSO, and BDS MEO satellite for 7d. When the residual information database initialization is complete, each satellite multipath error sequence model will be established from the residual database by using the low-pass filter method, then mitigating multipath error of the corresponding satellite carrier phase observations in real time. The measured data show that, based on the mitigating multipath of observation domain, the real-time monitoring accuracy of the 3D position can be improved by about 50% after mitigating multipath error in real-time.

The multipath error is the primary pseudorange measuring error factor in Compass system, in dual-frequency positioning mode, it is difficult to be eliminated by modeling methods, and on the contrary, it is always amplified because of the combination of measuring error. As a result, certain kind of user terminal has lower vertical positioning precision under dual-frequency mode than under single-frequency mode. This paper makes simulation of the impact of multipath error on pseudorange UERE under single-band mode and dual-band mode, obtains the interrelation of ionosphere modeling error, multipath error and the vertical positioning precision of single-band and dual-band respectively. This paper extracts multipath error in pseudorange of GEO and IGSO satellite by pseudorange carrier phase combination method, and uses the ionosphere delay calculated by dual-band carrier phase measurements as a benchmark, makes assessment of the ionosphere delay calculated by dual-band pseudorange combination method and ionospheric delay model correction method, analyses the amount of error correction brought into the Compass system by pseudorange of distinct orbit satellite. Data processing results show that, under current multipath mitigation measures, the pseudorange multipath error will cause that the error of GEO satellite ionosphere delay correction measured by dual-band is larger than by single-band, make a reasonable interpretation of the phenomena that dual-band vertical positioning accuracy is lower than single-band vertical positioning accuracy, and the ionospheric delay correction errors brought by pseudorange multipath error of GEO satellites are greater than the IGSO satellites, verify the phenomenon of “standing multipath error” brought by GEO satellite orbital characteristics.

Multipath effects are the most challenging error sources for the Global Navigation Satellite System receiver, affecting observation quality and positioning accuracy. Due to the non-linear and time-varying nature, multipath error is difficult to process. Previous studies used a homogeneous indicator to characterize multipath effects and only revealed the temporal or spatial correlations of the multipath, resulting in limited correction performance. In this study, we consider the code multipath to be influenced not only by the elevation and azimuth angle of certain stations to satellites but also to be related to satellite characteristics such as nadir angle. Hence, azimuth angle, elevation angle, nadir angle and carrier-to-noise power density ratio are taken as multiple indicators to characterize the multipath significantly. Then, we propose an Attention-based Convolutional Long Short-Term Memory (AT-Conv-LSTM) that fully exploits the spatiotemporal correlations of multipath derived from multiple indicators. The main processing procedures using AT-Conv-LSTM are given. Finally, the AT-Conv-LSTM is applied to a station for 16 consecutive days to verify the multipath mitigation effectiveness. Compared with sidereal filtering, multipath hemispherical map (MHM) and trend-surface analysis-based MHM, the experimental results show that using AT-Conv-LSTM can decrease the root mean square error and mean absolute error values of the multipath error more than 60% and 13%, respectively. The proposed method can correct the code multipath to centimeter level, which is one order of magnitude lower than the uncorrected code multipath. Therefore, the proposed AT-Conv-LSTM network could be used as a powerful alternative tool to realize multipath reduction and will be of wide practical value in the fields of standard and high-precision positioning services.

The objective was to compare case ascertainment, agreement, validity, and missing values for clinical research data obtained, processed, and linked electronically from electronic health records (EHR) compared to "manual" data processing and record abstraction in a cohort of out-of-hospital trauma patients. This was a secondary analysis of two sets of data collected for a prospective, population-based, out-of-hospital trauma cohort evaluated by 10 emergency medical services (EMS) agencies transporting to 16 hospitals, from January 1, 2006, through October 2, 2007. Eighteen clinical, operational, procedural, and outcome variables were collected and processed separately and independently using two parallel data processing strategies by personnel blinded to patients in the other group. The electronic approach included EHR data exports from EMS agencies, reformatting, and probabilistic linkage to outcomes from local trauma registries and state discharge databases. The manual data processing approach included chart matching, data abstraction, and data entry by a trained abstractor. Descriptive statistics, measures of agreement, and validity were used to compare the two approaches to data processing. During the 21-month period, 418 patients underwent both data processing methods and formed the primary cohort. Agreement was good to excellent (kappa = 0.76 to 0.97; intraclass correlation coefficient [ICC] = 0.49 to 0.97), with exact agreement in 67% to 99% of cases and a median difference of zero for all continuous and ordinal variables. The proportions of missing out-of-hospital values were similar between the two approaches, although electronic processing generated more missing outcomes (87 of 418, 21%, 95% confidence interval [CI] = 17% to 25%) than the manual approach (11 of 418, 3%, 95% CI = 1% to 5%). Case ascertainment of eligible injured patients was greater using electronic methods (n = 3,008) compared to manual methods (n = 629). In this sample of out-of-hospital trauma patients, an all-electronic data processing strategy identified more patients and generated values with good agreement and validity compared to traditional data collection and processing methods.

Research work is one of the most difficult types of independent work of applicants for the second level of higher education (master's students), the implementation of which requires special knowledge and skills. For master's cadets, preparing and writing a master's thesis is the first experience of research activity. In the Kherson State Maritime Academy, for master's cadets specializing in «Navigation and Management of Sea Vessels», the course «Modern Methods of Scientific Research and Data Processing» (MMSRDP) is provided, which, according to the curriculum and educational and professional program, is included in the cycle of professional training. The program of the academic discipline «Modern Methods of Scientific Research and Data Processing» is drawn up in accordance with the Code of Training, Certification and Watchkeeping for Seafarers STCW-78, IMO-MODEL COURSE 7.01, 7.03. and according to EPP. The direction of our research is to improve the teaching of the course «Modern Methods of Scientific Research and Data Processing» in the Kherson State Maritime Academy to achieve more significant standards of professional competence of applicants for the second level of higher education (master's students) in the specialization «Navigation and Management of Marine Vessels» of KhSMA. This article examines two of the most important components of the MMSRDP course. The first is the «starting» knowledge of the methodology and methods of scientific research, namely, the most significant classical paradigms that determine the essence of the concepts of methodology and methods of scientific research, concepts and issues of modern methods of empirical and theoretical research. The second, no less important component of the MMSRDP course is the study by master's students of specific methods and techniques of data processing and analysis. Our further research is aimed at a more detailed consideration of the second component of the MMSRDP course - the study by master's students of specific methods and techniques of data processing and analysis in the field of technical sciences, in particular, in the field of navigation, which are most necessary for master's students of the navigation specialty, as well as the development of a set of individual tasks for master's students aimed at the application of specific methods and techniques of data collection and analysis

The properties of geophones are important factors for high-resolution seismic exploration and have great influence on data quality. In this study we will address the problems of ultrashallow seismic data acquisition and processing. The purpose of our study is to evaluate the applicability of using different seismic geophones and processing techniques, to detect a thin soil layer about 20 cm in thickness under the depth of about 2 m in Liangzhu archaeological site, Southeastern China. We have collected seismic data with two kinds of geophones, normal geophones with different natural frequencies inserted into the ground, and towable cable geophones contacting the earth surface. We considered combining the frequency advantages of these two different kinds of geophones to broaden the effective bandwidth of the acquired data. To achieve this, we designed a partial frequency match filtering method in data processing which helps to improve the resolution of seismic reflected data. The result of stacking profiles shows that match filtering is effective in detecting a thin layer compared with drilling samples and other geophysical works.

Information and communications technologies today are used in virtually any university course when students prepare their papers. ICT is also needed after people are graduated from university and enter the job market. This author is an instructor in the field of informatics related to health care and social sciences at the Riga Stradiņs University. In practice, he has found that after completing informatics courses (IC) at the university level, students and practicing specialists at various levels find it hard to decide on what data processing method to use in order to interpret extracted results in the relevant area of specialisation. There are various data processing methods in the literature, presented individually and without adequate linkages. The author has found in practice that when such assignments are handled, there is closer linkage among data processing methods than the literature would suggest. In this article, the authors deal with the following issues: (1) how assignments given during informatics courses at the university level can be integrated with the relevant area of specialisation by making use of professional standards, guidebooks to studies in other courses, descriptions and scholarly publications so as to help students and practicing specialists to take decisions on data processing methods, their use, and the interpretation of their results; (2) how to ensure that educational data related to the area of specialisation are obtained on the basis of statistics in scholarly publications; (3) what kind of content is to be used for students of health care and the social sciences; (4) how to choose methods to resolve data processing issues; (5) what are the recommended principles for evaluating the knowledge, skills and talents of students? The views that are presented in this paper are those of the authors or of other authors.

Time‐lapse seismic data processing is an important technique for observing subsurface changes over time. The conventional time‐lapse seismic exploration has been conducted using a large‐scale exploration system. However, for efficient monitoring of shallow subsurface, time‐lapse monitoring based on the small‐scale exploration system is required. Small‐scale exploration system using a sparker source offers high vertical resolution and cost efficiency, but it faces challenges, such as inconsistent waveforms of sparker sources, inaccurate positioning information and a low signal‐to‐noise ratio. Therefore, this study proposes a data processing workflow to preserve the signal and enhance the repeatability of small‐scale time‐lapse seismic data acquired using a sparker source. The proposed workflow has three stages: pre‐stack, post‐stack and machine learning–based data processing. Conventional seismic data processing methods were applied to enhance the quality of the sparker seismic data during the pre‐stack data processing stage. In the post‐stack processing stage, the positions and energy correction were performed, and the machine learning–based data processing stage attenuated random noise and applied a matched filter. The data processing was performed using only the seismic signals recorded near the seafloor, and the results confirmed the improvement in the repeatability of the entire seismic profile, including that of the target area. According to the repeatability quantification results, the predictability increased and the normalized root mean square decreased during data processing, indicating improved repeatability. In particular, the repeatability of the data was greatly improved through vertical correction, energy correction and matched filtering approaches. The processing results demonstrate that the data processing method proposed in this study can effectively enhance the repeatability of high‐resolution time‐lapse seismic data. Consequently, this approach could contribute to a more accurate understanding of temporal changes in subsurface structure and material properties.

This paper, taking a match of the province of north China as an example, based on the schools for the past ten years and awards for qualitative and quantitative data analysis and processing. Then through the model to predict the next year, and on the basis of the present situation and awards by the normal given the competition for the school places allocation scheme, in order to improve the quality and efficiency. This paper presents a method and process of big data analysis and processing by using SPSS and MATLAB and other mathematical software based on actual cases. The prediction results are reliable and can be used for reference. The innovation of this paper is that the weight ratio of analytic hierarchy process is used as the reference for quota allocation. Its advantage is that it can make the allocation result more flexible and easy to be controlled artificially. In addition, the paper adopts arithmetic average method, geometric average method and eigenvalue method respectively in the weight calculation, and then takes the average weight of the three methods to make the result more robust.

Based on a large number of data generated by the application of the Internet of things, the data information is processed and processed. The contents and methods of data processing in three-tier IOT structure are different. Upper layer: data communication and data communication; data acquisition and application. The data processing process reflects the purpose and mode of data processing in the Internet of things system. A large number of experiments have proved that the data processing methods and forms used in this paper have practical significance.

In this article an attempt is made to remove some of the confusions that may block understanding of the digital computer, its use and its application to the surveying profession. An outline of the history of electronic data processing is given from the earliest concepts of numerical symbols and mechanical accounting machines to the present levels of technological skills. The various functional components that collectively form a data processing system are described in simple and non-technical terms. Data representation and storage devices are considered in order to introduce a typical data processing system. Data processing methods and user responsibilities are emphasized to highlight data processing justification. More importantly the article is intended to help surveyors understand the part that electronic data processing could play in the successful introduction of the “Integrated Survey System” into New South Wales. Hence the objective of this article is educational and informative rather than technically detailed.

Many factors affect the power load prediction which is worthy of attention in power production and management. The factors can be expressed as tensors. Most traditional forecasting models require the inputs are matrics. When the inputs are tensors, data processing is needed. In this paper, a data processing method which is called tensor partial least squares (TPLS) is proposed to transform the input tensor into matrix in the latent space. Two classical and commonly used methods, support vector machine (SVM) and back propagation neural network (PBNN), are selected to test the prediction results. Compared with the traditional data processing method, TPLS can improve the prediction accuracy.

Electromagnetic acoustic resonance method (EMAR) has a high capability of evaluating thickness or ultrasonic velocity, and it is applied to the measurement of thickness, elastic constants, damping properties and so on. Since the principle of the method is based on the through-thickness resonances of bulk waves, that is, thickness oscillations, targets are usually limited to ones with simple geometry such as plates. In this study, pipe wall thinning, where the thickness changes on the curved surface, is evaluated by EMAR. For the purpose, several data processing methods are applied to extract thickness information from spectral responses. Measured spectra are obtained by an experiment using a carbon steel pipe with two-dimensional thinning machined by milling, and results of the data processing are compared in view of accuracy and stability. Finally, the data processing method is applied to the EMAR spectra of a pipe specimen cut from a mock-up test loop.

The wide-field telescope will be an important tool in the discovery and birth of new theories of astronomy in future. The detectors in this kind of telescope mostly adopt a mosaic focal plane array. The focal depth of a large-F-number optical system is very small, and the flatness of the mosaic detector should be less than half the focal depth. In this paper, a new flatness measurement and data processing method is developed. A flatness measurement platform composed of a high-precision gantry platform and a coaxial multispectral displacement meter was built. The flatness of a single detector was measured under uncooled and cooled working conditions, and data processing was conducted, in which the root mean square (RMS) and the peak-valley (PV) values of the cooled detector were 0.0017 mm and 0.0112 mm, respectively. Next, a 2 × 6 mosaic model of the focal plane with a dimension of 148.5 mm × 168.5 mm was built using a metal detector model. The measurement platform was used to measure the flatness of the mosaic focal plane. According to the measurement results, the preliminary installation and mosaic adjustment were completed. The final RMS and PV values of the mosaic focal plane are 0.009 mm and 0.0808 mm, respectively. The experimental results show that the measurement and the data processing method can accurately reflect surface information on the detectors. This suggests that the method has great potential for use in ensuring the accuracy of wide-field telescope equipment in all applicable research areas.