Raw Observations Research Articles

Space-Wise approach for airborne gravity data modelling

Regional gravity field modelling by means of remove-compute-restore procedure is nowadays widely applied in different contexts: it is the most used technique for regional gravimetric geoid determination, and it is also used in exploration geophysics to predict grids of gravity anomalies (Bouguer, free-air, isostatic, etc.), which are useful to understand and map geological structures in a specific region. Considering this last application, due to the required accuracy and resolution, airborne gravity observations are usually adopted. However, due to the relatively high acquisition velocity, presence of atmospheric turbulence, aircraft vibration, instrumental drift, etc., airborne data are usually contaminated by a very high observation error. For this reason, a proper procedure to filter the raw observations in both the low and high frequencies should be applied to recover valuable information. In this work, a software to filter and grid raw airborne observations is presented: the proposed solution consists in a combination of an along-track Wiener filter and a classical Least Squares Collocation technique. Basically, the proposed procedure is an adaptation to airborne gravimetry of the Space-Wise approach, developed by Politecnico di Milano to process data coming from the ESA satellite mission GOCE. Among the main differences with respect to the satellite application of this approach, there is the fact that, while in processing GOCE data the stochastic characteristics of the observation error can be considered a-priori well known, in airborne gravimetry, due to the complex environment in which the observations are acquired, these characteristics are unknown and should be retrieved from the dataset itself. The presented solution is suited for airborne data analysis in order to be able to quickly filter and grid gravity observations in an easy way. Some innovative theoretical aspects focusing in particular on the theoretical covariance modelling are presented too. In the end, the goodness of the procedure is evaluated by means of a test on real data retrieving the gravitational signal with a predicted accuracy of about 0.4 mGal.

Mapping experience in reportage drawing

Abstract Reportage drawing is a revelatory act that combines the challenges of quick, gestural drawing with a level of accuracy in the depiction of people and places. Add to that the complications of working in sometimes hostile or, at the very least, less than ideal environments and you have a highly unique drawing act. Reportage drawing, through its quick execution necessitated by environmental flux and other conditions, also provides a window into the genesis of the drawing. The momentary, intuitive process fluctuates between the observed, the imagined and the remembered. Looking at the way in which the drawing is rooted to the in situ experience and notions of place, artists engage in reportage drawing in highly individual ways, balancing intent with the demands of observation in fluid environments. Experience here is twofold: the experience of negotiating the location and the experience of drawing itself. Through interviews conducted with reportage artists Jill Gibbon, Gary Embury as well as my own work and reflections, the aims and intentions of the artists will be compared and contrasted, and tensions between the journalistic and social commentary aims will be explored through individual practice. Jill Gibbon’s practice and research looks at the potential in reportage drawing for political, even radical, expression. Her War Mart work is explored here, which clearly reveals her reportage process, secretly drawing at an arms trading event in London and creating evocative commentary through her hurried, immediate drawings. Gary Embury is the editor of the Reportager website, which provides a crucial platform for contemporary reportage practice. His work is characterized by raw observation and his declared aims for his work are journalistic. This work has great immediacy and reveals the simultaneity between observation and action in drawing. Through a narrative of the experience creating their work in differing environments, the work will be seen as the summation of experience and the complex intentions and self-imposed limitations of the artists, contributing to an intimate look at contemporary reportage practice.

GPS observations of coseismic deformation following the 2016, August 24, Mw 6 Amatrice earthquake (central Italy): data, analysis and preliminary fault model

<p>We used continuous Global Positioning System (GPS) measurements to infer the fault geometry and the amount of coseismic slip associated to the August 24, 2016 Mw 6 Amatrice earthquake. We realized a three dimensional coseismic displacement field by combining different geodetic solutions generated by three independent analyses of the raw GPS observations. The coseismic deformation field described in this work aims at representing a consensus solution that minimizes the systematic biases potentially present in the individual geodetic solutions. Because of the limited number of stations available we modeled the measured coseismic displacements using a uniform slip model, deriving the geometry and kinematics of the causative fault, finding good agreement between our geodetically derived fault plane and other seismological and geological observations. <strong></strong></p>

Multi-GNSS precise point positioning (MGPPP) using raw observations

A joint-processing model for multi-GNSS (GPS, GLONASS, BDS and GALILEO) precise point positioning (PPP) is proposed, in which raw code and phase observations are used. In the proposed model, inter-system biases (ISBs) and GLONASS code inter-frequency biases (IFBs) are carefully considered, among which GLONASS code IFBs are modeled as a linear function of frequency numbers. To get the full rank function model, the unknowns are re-parameterized and the estimable slant ionospheric delays and ISBs/IFBs are derived and estimated simultaneously. One month of data in April, 2015 from 32 stations of the International GNSS Service (IGS) Multi-GNSS Experiment (MGEX) tracking network have been used to validate the proposed model. Preliminary results show that RMS values of the positioning errors (with respect to external double-difference solutions) for static/kinematic solutions (four systems) are 6.2 mm/2.1 cm (north), 6.0 mm/2.2 cm (east) and 9.3 mm/4.9 cm (up). One-day stabilities of the estimated ISBs described by STD values are 0.36 and 0.38 ns, for GLONASS and BDS, respectively. Significant ISB jumps are identified between adjacent days for all stations, which are caused by the different satellite clock datums in different days and for different systems. Unlike ISBs, the estimated GLONASS code IFBs are quite stable for all stations, with an average STD of 0.04 ns over a month. Single-difference experiment of short baseline shows that PPP ionospheric delays are more precise than traditional leveling ionospheric delays.

Absolute gravity observations in Norway (1993–2014) for glacial isostatic adjustment studies: The influence of gravitational loading effects on secular gravity trends

We have compiled and analyzed FG5 absolute gravity observations between 1993 and 2014 at 21 gravity sites in Norway, and explore to what extent these observations are applicable for glacial isostatic adjustment (GIA) studies. Where available, raw gravity observations are consistently reprocessed. Furthermore, refined gravitational corrections due to ocean tide loading and non-tidal ocean loading, as well as atmospheric and global hydrological mass variations are computed. Secular gravity trends are computed using both standard and refined corrections and subsequently compared with modeled gravity rates based on a GIA model. We find that the refined gravitational corrections mainly improve rates where GIA, according to model results, is not the dominating signal. Consequently, these rates may still be considered unreliable for constraining GIA models, which we trace to continued lack of a correction for the effect of local hydrology, shortcomings in our refined modeling of gravitational effects, and scarcity of observations. Finally, a subset of standard and refined gravity rates mainly reflecting GIA is used to estimate ratios between gravity and height rates of change by ordinary and weighted linear regression. Relations based on both standard and refined gravity rates are within the uncertainty of a recent modeled result.

Nordic Snow Radar Experiment

Abstract. The objective of the Nordic Snow Radar Experiment (NoSREx) campaign was to provide a continuous time series of active and passive microwave observations of snow cover at a representative location of the Arctic boreal forest area, covering a whole winter season. The activity was a part of Phase A studies for the ESA Earth Explorer 7 candidate mission CoReH2O (Cold Regions Hydrology High-resolution Observatory). The NoSREx campaign, conducted at the Finnish Meteorological Institute Arctic Research Centre (FMI-ARC) in Sodankylä, Finland, hosted a frequency scanning scatterometer operating at frequencies from X- to Ku-band. The radar observations were complemented by a microwave dual-polarization radiometer system operating from X- to W-bands. In situ measurements consisted of manual snow pit measurements at the main test site as well as extensive automated measurements on snow, ground and meteorological parameters. This study provides a summary of the obtained data, detailing measurement protocols for each microwave instrument and in situ reference data. A first analysis of the microwave signatures against snow parameters is given, also comparing observed radar backscattering and microwave emission to predictions of an active/passive forward model. All data, including the raw data observations, are available for research purposes through the European Space Agency and the Finnish Meteorological Institute. A consolidated dataset of observations, comprising the key microwave and in situ observations, is provided through the ESA campaign data portal to enable easy access to the data.

Improved ambiguity resolution for URTK with dynamic atmosphere constraints

Raw observation processing method with prior knowledge of ionospheric delay could strengthen the ambiguity resolution (AR), but it does not make full use of the relatively longer wavelength of wide-lane (WL) observation. Furthermore, the accuracy of calculated atmospheric delays from the regional augmentation information has quite different in quality, while the atmospheric constraint used in the current methods is usually set to an empirical value. A proper constraint, which matches the accuracy of calculated atmospheric delays, can most effectively compensate the residual systematic biases caused by large inter-station distances. Therefore, the standard deviation of the residual atmospheric parameters should be fine-tuned. This paper presents an atmosphere-constrained AR method for undifferenced network RTK (URTK) rover, whose ambiguities are sequentially fixed according to their wavelengths. Furthermore, this research systematically analyzes the residual atmospheric error and finds that it mainly varies along the positional relationship between the rover and the chosen reference stations. More importantly, its ionospheric part of certain location will also be cyclically influenced every day. Therefore, the standard deviation of residual ionospheric error can be modeled by a daily repeated cosine or other functions with the help of data one day before, and applied by rovers as pseudo-observation. With the data collected at 29 stations from a continuously operating reference station network in Guangdong Province (GDCORS) in China, the efficiency of the proposed approach is confirmed by improving the success and error rates of AR for 10-20 % compared to that of the WL-L1-IF one, as well as making much better positioning accuracy.

An inversion method for cometary atmospheres

Remote observation of cometary atmospheres produces a measurement of the cometary emissions integrated along the line of sight. This integration is the so-called Abel transform of the local emission rate. The observation is generally interpreted under the hypothesis of spherical symmetry of the coma. Under that hypothesis, the Abel transform can be inverted. We derive a numerical inversion method adapted to cometary atmospheres using both analytical results and least squares fitting techniques. This method, derived under the usual hypothesis of spherical symmetry, allows us to retrieve the radial distribution of the emission rate of any unabsorbed emission, which is the fundamental, physically meaningful quantity governing the observation. A Tikhonov regularization technique is also applied to reduce the possibly deleterious effects of the noise present in the observation and to warrant that the problem remains well posed. Standard error propagation techniques are included in order to estimate the uncertainties affecting the retrieved emission rate. Several theoretical tests of the inversion techniques are carried out to show its validity and robustness. In particular, we show that the Abel inversion of real data is only weakly sensitive to an offset applied to the input flux, which implies that the method, applied to the study of a cometary atmosphere, is only weakly dependent on uncertainties on the sky background which has to be subtracted from the raw observations of the coma. We apply the method to observations of three different comets observed using the TRAPPIST telescope: 103P/ Hartley 2, F6/ Lemmon and A1/ Siding Spring. We show that the method retrieves realistic emission rates, and that characteristic lengths and production rates can be derived from the emission rate for both CN and C2 molecules. We show that the retrieved characteristic lengths can differ from those obtained from a direct least squares fitting over the observed flux of radiation, and that discrepancies can be reconciled for by correcting this flux by an offset (to which the inverse Abel transform is nearly not sensitive). The A1/Siding Spring observations were obtained very shortly after the comet produced an outburst, and we show that the emission rate derived from the observed flux of CN emission at 387nm and from the C2 emission at 514.1nm both present an easily-identifiable shoulder that corresponds to the separation between pre- and post-outburst gas. As a general result, we show that diagnosing properties and features of the coma using the emission rate is easier than directly using the observed flux, because the Abel transform produces a smoothing that blurs the signatures left by features present in the coma. We also determine the parameters of a Haser model fitting the inverted data and fitting the line-of-sight integrated observation, for which we provide the exact analytical expression of the line-of-sight integration of the Haser model.

Accounting for correlated observations in an age-based state-space stock assessment model

Abstract Fish stock assessment models often rely on size- or age-specific observations that are assumed to be statistically independent of each other. In reality, these observations are not raw observations, but rather they are estimates from a catch-standardization model or similar summary statistics based on observations from many fishing hauls and subsamples of the size and age composition of the data. Although aggregation mitigates the strong intra-haul correlation between sizes/ages that is usually found in haul-by-haul data, violations of the independence assumption can have a large impact on the results and specifically on reported confidence bounds. A state-space assessment model that allows for correlations between age groups within years in the observation model for catches and surveys is presented and applied to data on several North Sea fish stocks using various correlation structures. In all cases the independence assumption is rejected. Less fluctuating estimates of the fishing mortality is obtained due to a reduced process error. The improved model does not suffer from correlated residuals unlike the independent model, and the variance of forecasts is decreased.

MP37-16 UROLOGIST USE OF CYSTOSCOPY FOR PATIENTS PRESENTING WITH HEMATURIA

You have accessJournal of UrologyGeneral & Epidemiological Trends & Socioeconomics: Practice Patterns, Quality of Life and Shared Decision Making IV1 Apr 2016MP37-16 UROLOGIST USE OF CYSTOSCOPY FOR PATIENTS PRESENTING WITH HEMATURIA Samuel David, Datta Patil, Mehrdad Alemozaffar, Muta Issa, Viraj Master, and Christopher Filson Samuel DavidSamuel David More articles by this author , Datta PatilDatta Patil More articles by this author , Mehrdad AlemozaffarMehrdad Alemozaffar More articles by this author , Muta IssaMuta Issa More articles by this author , Viraj MasterViraj Master More articles by this author , and Christopher FilsonChristopher Filson More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2016.02.1693AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES In order to rule out a diagnosis of bladder cancer, performance of cystoscopy is an integral component of any guideline-congruent evaluation of a patient presenting with hematuria. Prior studies at a population-level were restricted to select populations (e.g., Medicare-eligible patients) or individual institutions. We used a population-representative survey to evaluate factors associated with use of cystoscopy among patients presenting to urologists with hematuria in the United States. METHODS Using the Center for Disease Control and Prevention National Ambulatory Medical Care Survey (2006-2010, 2012), we identified visits to urologists that resulted in a hematuria diagnosis, based on ICD-9-DM diagnosis codes 599.70, 599.71, or 599.72. After excluding visits with a urinary tract infection (UTI) diagnosis, we generated population-level estimates of cystoscopy use across the United States. Bivariate statistics and multivariable logistic regression were performed to evaluate the relationship between available patient (e.g., age, sex, tobacco use), provider (e.g., specialty, type of degree), and practice setting factors (e.g., region) and use of cystoscopy. Results were considered reliable if based on ≥30 raw observations or if standard errors were < 30% of point estimates. RESULTS Among an estimated 121 million patient visits to urologists, we identified >8.6 million encounters (95% CI 7.2-10.1 million) resulting in a hematuria diagnosis (in absence of UTI). Cystoscopy was performed or ordered after 35.9% (95% CI 31.6-40.4%) of these visits. Use of cystoscopy was more common among older patients (odds ratio (OR) 1.15 per 10 years of age, 95% CI 1.03-1.29) and current smokers (50.9% vs 33.1% non-smokers, OR 2.00, 95% CI 1.15-3.50) (Figure). Use of cystoscopy did not vary based on patient sex (39.9% female vs. 33.4% male, OR 1.40, 95% CI 0.89-2.20, p=0.14). CONCLUSIONS Despite guidelines emphasizing the importance of cystoscopy in the workup of hematuria, just over one-third of patients diagnosed with hematuria by urologists undergo this procedure. Although increased use of cystoscopy for smokers and older patients is encouraging, efforts should focus on increasing adherence to contemporary practice guidelines. © 2016FiguresReferencesRelatedDetails Volume 195Issue 4SApril 2016Page: e503 Advertisement Copyright & Permissions© 2016MetricsAuthor Information Samuel David More articles by this author Datta Patil More articles by this author Mehrdad Alemozaffar More articles by this author Muta Issa More articles by this author Viraj Master More articles by this author Christopher Filson More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

SELECCIÓN DE CARACTERÍSTICAS BASADAS EN ENTROPÍA CONDICIONAL PARA LA DETECCIÓN DE AVERÍAS EN CIRCUITOS ANALÓGICOS

ABSTRACT: To detect parametric faults in analog circuits, a novel feature selection algorithm based on conditional entropy, which was integrated with a support vector machine (SVM)-based fault detection approach, was proposed in this study. In preventing the significant loss of the effective features, a sampling process was executed with a significantly higher frequency. The side effect of this process showed that raw observation vectors were of extremely high dimensions. To reduce computation overhead, the feature selection algorithm based on conditional entropy was put forward to compress raw observation vectors into new observation vectors. The conditional entropy was used to update the conditional probability of a fault based on new fault information, which eventually made the fault probability more clear. By applying the proposed feature selection algorithm, it can compress raw data more wisely, and maximize the information in choosing the dimensions to be included in the new observation vectors. Simulation results showed that the fault detection approach presented in the study could classify non-linear feature vector space of the analog circuits. and achieved a lower misclassification rate than other current methods (i.e., equidistant method and conditional probability-based method). Keywords:Fault detection, Conditional entropy, Support vector machine (SVM), Classification

Preprocessing of centred logratio transformed density functions using smoothing splines

With large-scale database systems, statistical analysis of data, occurring in the form of probability distributions, becomes an important task in explorative data analysis. Nevertheless, due to specific properties of density functions, their proper statistical treatment of these data still represents a challenging task in functional data analysis. Namely, the usual metric does not fully accounts for the relative character of information, carried by density functions; instead, their geometrical features are captured by Bayes spaces of measures. The easiest possibility of expressing density functions in an space is to use centred logratio transformation, even though this results in functional data with a constant integral constraint that needs to be taken into account in further analysis. While theoretical background for reasonable analysis of density functions is already provided comprehensively by Bayes spaces themselves, preprocessing issues still need to be developed. The aim of this paper is to introduce optimal smoothing splines for centred logratio transformed density functions that take all their specific features into account and provide a concise methodology for reasonable preprocessing of raw (discretized) distributional observations. Theoretical developments are illustrated with a real-world data set from official statistics and with a simulation study.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

Multi-GNSS precise point positioning with raw single-frequency and dual-frequency measurement models

The emergence of multiple satellite navigation systems, including BDS, Galileo, modernized GPS, and GLONASS, brings great opportunities and challenges for precise point positioning (PPP). We study the contributions of various GNSS combinations to PPP performance based on undifferenced or raw observations, in which the signal delays and ionospheric delays must be considered. A priori ionospheric knowledge, such as regional or global corrections, strengthens the estimation of ionospheric delay parameters. The undifferenced models are generally more suitable for single-, dual-, or multi-frequency data processing for single or combined GNSS constellations. Another advantage over ionospheric-free PPP models is that undifferenced models avoid noise amplification by linear combinations. Extensive performance evaluations are conducted with multi-GNSS data sets collected from 105 MGEX stations in July 2014. Dual-frequency PPP results from each single constellation show that the convergence time of undifferenced PPP solution is usually shorter than that of ionospheric-free PPP solutions, while the positioning accuracy of undifferenced PPP shows more improvement for the GLONASS system. In addition, the GLONASS undifferenced PPP results demonstrate performance advantages in high latitude areas, while this impact is less obvious in the GPS/GLONASS combined configuration. The results have also indicated that the BDS GEO satellites have negative impacts on the undifferenced PPP performance given the current "poor" orbit and clock knowledge of GEO satellites. More generally, the multi-GNSS undifferenced PPP results have shown improvements in the convergence time by more than 60 % in both the single- and dual-frequency PPP results, while the positioning accuracy after convergence indicates no significant improvements for the dual-frequency PPP solutions, but an improvement of about 25 % on average for the single-frequency PPP solutions.

A reporting protocol for thermochronologic modeling illustrated with data from the Grand Canyon

Apatite (U–Th)/He and fission-track dates, as well as 4He/3He and fission-track length data, provide rich thermal history information. However, numerous choices and assumptions are required on the long road from raw data and observations to potentially complex geologic interpretations. This paper outlines a conceptual framework for this path, with the aim of promoting a broader understanding of how thermochronologic conclusions are derived. The tiered structure consists of thermal history model inputs at Level 1, thermal history model outputs at Level 2, and geologic interpretations at Level 3. Because inverse thermal history modeling is at the heart of converting thermochronologic data to interpretation, for others to evaluate and reproduce conclusions derived from thermochronologic results it is necessary to publish all data required for modeling, report all model inputs, and clearly and completely depict model outputs. Here we suggest a generalized template for a model input table with which to arrange, report and explain the choice of inputs to thermal history models. Model inputs include the thermochronologic data, additional geologic information, and system- and model-specific parameters. As an example we show how the origin of discrepant thermochronologic interpretations in the Grand Canyon can be better understood by using this disciplined approach.

Structure-Induced Complex Kalman Filter for Decentralized Sequential Bayesian Estimation

The letter considers a multi-sensor state estimation problem configured in a decentralized architecture where local complex statistics are communicated to the central processing unit for fusion instead of the raw observations. Naive adaptation of the augmented complex statistics to develop a decentralized state estimation algorithm results in increased local computations, and introduces extensive communication overhead, making it practically unattractive. The letter proposes a structure-induced complex Kalman filter framework with reduced communication overhead. In order to further reduce the local computations, the letter proposes a non-circularity criterion which allows each node to examine the non-circularity of its local observations. A local sensor node disregards its extra second-order statistical information when the non-circularity coefficient is small. In cases where the local observations are highly non-circular, an intuitively pleasing circularization approach is proposed to avoid computation and communication of the pseudo-covariance matrices. Simulation results indicate that the proposed structured-induced complex Kalman filter (SCKF) provides significant performance improvements over its traditional counterparts.

A collection of sub-daily pressure and temperature observations for the early instrumental period with a focus on the &amp;quot;year without a summer&amp;quot; 1816

Abstract. The eruption of Mount Tambora (Indonesia) in April 1815 is the largest documented volcanic eruption in history. It is associated with a large global cooling during the following year, felt particularly in parts of Europe and North America, where the year 1816 became known as the "year without a summer". This paper describes an effort made to collect surface meteorological observations from the early instrumental period, with a focus on the years of and immediately following the eruption (1815–1817). Although the collection aimed in particular at pressure observations, correspondent temperature observations were also recovered. Some of the series had already been described in the literature, but a large part of the data, recently digitised from original weather diaries and contemporary magazines and newspapers, is presented here for the first time. The collection puts together more than 50 sub-daily series from land observatories in Europe and North America and from ships in the tropics. The pressure observations have been corrected for temperature and gravity and reduced to mean sea level. Moreover, an additional statistical correction was applied to take into account common error sources in mercury barometers. To assess the reliability of the corrected data set, the variance in the pressure observations is compared with modern climatologies, and single observations are used for synoptic analyses of three case studies in Europe. All raw observations will be made available to the scientific community in the International Surface Pressure Databank.

Single-frequency precise point positioning: an analytical approach

An analytical approach to single-frequency precise point positioning (PPP) is discussed in this paper. To obtain highest precision results, all biases must be eliminated or modelled to centimetre level. The use of the GRAPHIC ionosphere-free linear combination that is based on single-frequency phase and code observations eliminates the ionosphere bias; however, the rank deficient Gauss–Markov model is obtained. We explicitly determine rank deficiency of a Gauss–Markov model as a number of all ambiguity clusters, each of them defined as a set of all ambiguities overlapping in time. On the basis of S-transformation we prove that the single-frequency PPP represents an unbiased estimator for station coordinates and troposphere parameters, while it presents a biased estimator for ambiguities and receiver-clock error parameters. Additionally we describe the estimable parameters in each ambiguity cluster as the differences between ambiguity parameters and the sum of receiver-clock parameters with one of the ambiguities. We also show that any other particular solution on the basis of S-transformation is obtained only when the common least-squares estimation in single step is applied. The recursive least-squares estimation with parameter pre-elimination only determines the vector of unknowns as possible to transform through S-transformation, whereas the same does not hold for the cofactor matrix of unknowns. For a case study, we present our method on GPS data from 19 permanent stations (14 IGS and 5 EPN) in Europe, for 89 consecutive days in the beginning of 2013. The static case study revealed the precision of daily coordinates as 7.6, 11.7 and 19.6 mm for \(N\), \(E\) and \(U\), respectively. The accuracies of the \(N\), \(E\) and \(U\) components were determined as 6.9, 13.5 and 31.4 mm, respectively, and were calculated using the Helmert transformation of weighted-mean daily single-frequency PPP and IGb08 coordinates. The estimated convergence times were relatively diverse, expanding from 1.75 h (CAGL) to 5.25 h (GRAZ) for the horizontal position with the 10-cm precision threshold, and from 1.00 h (GRAS) to 3.25 h (BZRG) for the height component with a 20-cm precision threshold. The convergence times were shown to be strongly correlated to the remaining unmodelled biases in the GRAPHIC linear combination, primarily with multipath, where the correlation coefficient for the horizontal position was determined as \(\rho _P\) \(=\) 0.68 and for height as \(\rho _U\) \(=\) 0.85. The comparison to the model where raw observations are used (\(C\), \(L\)) and where the ionosphere bias is mitigated with global ionosphere models (GIM) revealed the supremacy of the proposed single-frequency PPP method based on the GRAPHIC linear combination in both the static and the semi-kinematic case study. In the static case study, the proposed single-frequency PPP model was superior both in terms of precision and accuracy. In the semi-kinematic case study, the usage of raw observations with GIM would improve results only when multipath and noise of code observations would prevail over the remaining ionosphere bias, i.e. after applying GIM.

Experience from geodetic very long baseline interferometry observations at Onsala using a digital backend

Abstract The Onsala Space Observatory has installed a modern digital backend for geodetic and astronomical Very Long Baseline Interferometry (VLBI). This system consists of a Digital Base-Band Converter (DBBC) and a Mark 5B+ recorder. From 2011 until late 2014 this new system was run for geodetic VLBI observations in parallel with the old system consisting of a Mark 4 rack and Mark 5A recording system. Several of these observed sessions were correlated at the correlator in Bonn including both data sets. We present results from the analysis and comparison of these sessions. Both the original observed delays and corresponding geodetic parameters are compared. No significant differences are detected, for either the raw observations or for the geodetic parameters. This shows that the digital backend can be used operationally for geodetic VLBI observations.

Tightly coupled integration of ionosphere-constrained precise point positioning and inertial navigation systems.

The continuity and reliability of precise GNSS positioning can be seriously limited by severe user observation environments. The Inertial Navigation System (INS) can overcome such drawbacks, but its performance is clearly restricted by INS sensor errors over time. Accordingly, the tightly coupled integration of GPS and INS can overcome the disadvantages of each individual system and together form a new navigation system with a higher accuracy, reliability and availability. Recently, ionosphere-constrained (IC) precise point positioning (PPP) utilizing raw GPS observations was proven able to improve both the convergence and positioning accuracy of the conventional PPP using ionosphere-free combined observations (LC-PPP). In this paper, a new mode of tightly coupled integration, in which the IC-PPP instead of LC-PPP is employed, is implemented to further improve the performance of the coupled system. We present the detailed mathematical model and the related algorithm of the new integration of IC-PPP and INS. To evaluate the performance of the new tightly coupled integration, data of both airborne and vehicle experiments with a geodetic GPS receiver and tactical grade inertial measurement unit are processed and the results are analyzed. The statistics show that the new approach can further improve the positioning accuracy compared with both IC-PPP and the tightly coupled integration of the conventional PPP and INS.