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  • Allan variance  (1)
  • Generalized expectation maximization algorithm  (1)
  • Englisch  (2)
  • 1
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    Performance of miniaturized atomic clocks in static laboratory and dynamic flight environments (2020)
    Springer Berlin Heidelberg
    Details
    Publikationsdatum: 2023-06-16
    Beschreibung: Miniaturized atomic clocks with high frequency stability as local oscillators in global navigation satellite system (GNSS) receivers promise to improve real-time kinematic applications. For a number of years, such oscillators are being investigated regarding their overall technical applicability, i.e., transportability, and performance in dynamic environments. The short-term frequency stability of these clocks is usually specified by the manufacturer, being valid for stationary applications. Since the performance of most oscillators is likely degraded in dynamic conditions, various oscillators are tested to find the limits of receiver clock modeling in dynamic cases and consequently derive adequate stochastic models to be used in navigation. We present the performance of three different oscillators (Microsemi MAC SA.35m, Spectratime LCR-900 and Stanford Research Systems SC10) for static and dynamic applications. For the static case, all three oscillators are characterized in terms of their frequency stability at Physikalisch-Technische Bundesanstalt, Germany's national metrology institute. The resulting Allan deviations agree well with the manufacturer's data. Furthermore, a flight experiment was conducted in order to evaluate the performance of the oscillators under dynamic conditions. Here, each oscillator is replacing the internal oscillator of a geodetic-grade GNSS receiver and the stability of the receiver clock biases is determined. The time and frequency offsets of the oscillators are characterized with regard to the flight dynamics recorded by a navigation-grade inertial measurement unit. The results of the experiment show that the frequency stability of each oscillator is degraded by about at least one order of magnitude compared to the static case. Also, the two quartz oscillators show a significant g-sensitivity resulting in frequency shifts of − 1.2 × 10−9 and + 1.5 × 10−9, respectively, while the rubidium clocks are less sensitive, thus enabling receiver clock modeling and strengthening of the navigation performance even in high dynamics.
    Beschreibung: Bundesministerium für Wirtschaft und Energie http://dx.doi.org/10.13039/501100006360
    Beschreibung: Gottfried Wilhelm Leibniz Universität Hannover (1038)
    Schlagwort(e): ddc:526 ; Allan variance ; Miniaturized atomic clocks ; Frequency stability ; Flight navigation ; GNSS
    Sprache: Englisch
    Materialart: doc-type:article
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    CITATION GEO-LEO
  • 2
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    Self-tuning robust adjustment within multivariate regression time series models with vector-autoregressive random errors (2020)
    Springer Berlin Heidelberg
    Details
    Publikationsdatum: 2023-07-03
    Beschreibung: The iteratively reweighted least-squares approach to self-tuning robust adjustment of parameters in linear regression models with autoregressive (AR) and t-distributed random errors, previously established in Kargoll et al. (in J Geod 92(3):271–297, 2018. https://doi.org/10.1007/s00190-017-1062-6), is extended to multivariate approaches. Multivariate models are used to describe the behavior of multiple observables measured contemporaneously. The proposed approaches allow for the modeling of both auto- and cross-correlations through a vector-autoregressive (VAR) process, where the components of the white-noise input vector are modeled at every time instance either as stochastically independent t-distributed (herein called “stochastic model A”) or as multivariate t-distributed random variables (herein called “stochastic model B”). Both stochastic models are complementary in the sense that the former allows for group-specific degrees of freedom (df) of the t-distributions (thus, sensor-component-specific tail or outlier characteristics) but not for correlations within each white-noise vector, whereas the latter allows for such correlations but not for different dfs. Within the observation equations, nonlinear (differentiable) regression models are generally allowed for. Two different generalized expectation maximization (GEM) algorithms are derived to estimate the regression model parameters jointly with the VAR coefficients, the variance components (in case of stochastic model A) or the cofactor matrix (for stochastic model B), and the df(s). To enable the validation of the fitted VAR model and the selection of the best model order, the multivariate portmanteau test and Akaike’s information criterion are applied. The performance of the algorithms and of the white noise test is evaluated by means of Monte Carlo simulations. Furthermore, the suitability of one of the proposed models and the corresponding GEM algorithm is investigated within a case study involving the multivariate modeling and adjustment of time-series data at four GPS stations in the EUREF Permanent Network (EPN).
    Beschreibung: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Schlagwort(e): ddc:526 ; Regression time series ; Vector-autoregressive model ; Cross-correlations ; Multivariate scaled t-distribution ; Self-tuning robust estimator ; Generalized expectation maximization algorithm ; Iteratively reweighted least squares ; Multivariate portmanteau test ; Monte Carlo simulation ; GPS time series
    Sprache: Englisch
    Materialart: doc-type:article
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    CITATION GEO-LEO
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