StudiumLehrveranstaltungen
Selected Topics of Geodetic Data Analysis

Selected Topics of Geodetic Data Analysis

This module provides advanced knowledge about concepts and principles of geodetic data analysis in the fields of robust parameter estimation and Bayesian statistics, as well as techniques for modeling, adjusting and analysing geodetic data sets based on an application of these concepts and principles.

After successful completion of this module, the students are able to give an overview of typical robust and Bayesian methods of geodetic analysis, to explain the principles of and suitable algorithms for robust as well as Bayesian methods, to apply robust and Bayesian adjustment techniques to data sets, to analyse application problems with regard to adequate robust and Bayesian observation models and to interpret adjustment results correctly obtained from robust and Bayesian methods.

MODULE CONTENTS

  • Principles of robust parameter estimation
  • M-estimators (L2-norm, L1-norm and Huber’s estimator); iteratively reweighted least squares
  • RANSAC algorithm
  • Bayesian strategies and Bayesian parameter estimation
  • Generating random numbers
  • Monte Carlo techniques (Monte Carlo integration and Markov Chain Monte Carlo)

LECTURER

Dr.-Ing. Hamza Alkhatib
Adresse
Nienburger Straße 1
30167 Hannover
Gebäude
Raum
Dr.-Ing. Hamza Alkhatib
Adresse
Nienburger Straße 1
30167 Hannover
Gebäude
Raum

EXERCISE

M. Sc. Alexander Dorndorf
Adresse
Nienburger Straße 1 (B123)
30167 Hannover
M. Sc. Alexander Dorndorf
Adresse
Nienburger Straße 1 (B123)
30167 Hannover