Geodetic Data Analysis

Abstract

The lecture provides knowledge about the planning, computation and analysis of geodetic networks, as well as the use of data analysis methods in geodesy in general. The necessary mathematical and statistical methods are presented and applied using examples from geodesy.

Objective

After completing this course, the participants should be equipped with the necessary tools to plan, analyze and evalute geodetic networks as well as to evaluate and analyze geodetic data in general. For typical geodetic tasks the participants should be able to provide concepts of solutions as well as to do the necessary programming work.

Content

Recapitulation of basics in statistics and probability theory (density and distribution functions, random variables, correlations, Monte Carlo simulation, hypothesis tests), linear and nonlinear least squares estimation, terrestrial and satellite-based observation equations, reference frames and transformations (global, local, astronomical), geodetic datum (free/constrained networks, full/partial trace minimization), quality control of geodetic methods (precision, reliability), robust estimation, time series analysis (decomposition, stochastic processes, parametric/nonparametric methods, regression models, spectral analysis and filtering, significance tests), basics of Kalman filtering (state space representation, Kalman equations, quality control)

Resources