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- W2183632204 abstract "Signal distortion by multipath and diffraction is hardly avoidable in engineering applications of GPS, like deformation monitoring, machine guidance or setting out of points on a construction site. With kinematic GPS or short static sessions these effects may result in cm-level biases in the coordinate estimates, if not taken into account properly. In this paper, a two-step fuzzy system is presented, which controls the parameter estimation by iteratively reweighted least squares (RLS) and assesses the quality of the estimates. The robust RLS estimation yields least squares results if no signal distortion is present. In all other cases, it helps to obtain the best possible estimate using the biased data. This is accomplished by a fuzzy system that combines conventional outlier detection with additional information on the data quality, e.g. the S/N. Subsequently, the quality of the estimates is rated. The rating is based on the redundancy, the accuracy (confidence ellipsoid) and the reliability. Insufficiently accurate or unreliable epochs are flagged. We demonstrate the benefits of the two-step fuzzy system using real GPS data from an experiment. We focus on single epoch processing because of its sensitivity to biased data. Once the ambiguities are fixed, mm-level accuracy is obtainable even during signal distortion periods using non-filtered epoch-by-epoch processing." @default.
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- W2183632204 date "2001-09-14" @default.
- W2183632204 modified "2023-09-28" @default.
- W2183632204 title "A Fuzzy System for Robust Estimation and Quality Assessment of GPS Data for Real-Time Applications" @default.
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