GNSS vector quality modelling combining Isolation Forest and Independent Vortices Search

Abstract

Estimating the quality of GNSS vectors is decisive in planning GNSS networks and in several land surveying activities. These vectors are indirectly present in many civil infrastructures usually in the first stages of constructions and thus of high importance. In this research we assembled over 1000 baselines producing an extensive database with over 170,000 processed vectors. We propose a novel identification of outlying GNSS vectors based on the Isolation Forest (IF) algorithm based on the vectors deviations. And a new procedure to build linear models based on metaheuristics and a penalty function. The linear regressions presented models with a coefficient of determination R2 up to 0.996. The observation time span variable remained in all equations at least twice, showing its importance for the outcome quality of a vector. Overall, the three-dimensional deviation of vectors processed with broadcast ephemeris is 2.4 times higher than for precise ephemerides.