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EN
The GNSS positioning performance is commonly defined and described in terms unspecified to particular GNSS-based application. The approach causes difficulties to GNSS application developers, operators, and users, rendering the impact assessment of GNSS performance on the GNSS application Quality of Service (QoS) particularly difficult. Here the Probability of Occurrence (PoO) Model is introduced, which allows for a risk assessment of the probability for the GNSS positioning accuracy failure to meet the requirements of the particular GNSS-based application. The proposed PoO Model development procedure requires a large set of position estimation errors observations, which shall cover a range of classes of positioning environment (space weather, troposphere, multi-path etc.) disturbances affecting GNSS positioning accuracy. As result, the PoO Model becomes a tool that returns the probability of failure in meeting the positioning accuracy requirements of the GNSS applications considered, thus providing the input for a GNSS deployment risk assessment. The proposed PoO Model and its development procedure are demonstrated in the case of polar region positioning environment, with raw GNSS pseudorange observations taken at the International GNSS Service (IGS) Network reference station Iqualuit, Canada are used for the PoO Model development. The PoO Model proof-of-principle is then used to estimate the probability of the unmet required positioning accuracy for a number of polar maritime navigation applications. Manuscript concludes with a discussion of the PoO Model benefits and shortcomings, a summary of contribution, and intentions for the future research.
EN
Provision of uninterrupted and robust Positioning, Navigation, and Timing (PNT) services is essential task of Global Navigation Satellite Systems (GNSS) as an enabling technology for numerous technology and socio-economic applications, a cornerstone of the modern civilisation, a public goods, and an essential component of a national infrastructure. GNSS resilience may be accomplished only with complete understanding of the causes of GNSS positioning performance disruptions and degradations, presented in a form of applications- and scenarios-related models. Here the application of change-point detection methods is proposed and demonstrated in a selected scenario of a fast-developing ionospheric storm’s impact on GNSS positioning performance, as a novel contribution to forecasting GNSS positioning performance model development and GNSS utilisation risk mitigation.
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