Single-Course English 5 ECTS

Global Navigation Satellite Systems

Overall Course Objectives

Accurate and reliable positioning has become increasingly important for the navigation of vehicles, drones and autonomous systems. Global satellite-based positioning systems play a key role in fulfilling that need.

The course aims to give a solid knowledge about global navigation satellite systems, how the systems work, and how accurate positions may be obtained. In addition, the course provides a good knowledge of the mathematical modelling principles used for both code and phase-based GNSS positioning (GPS, Galileo, or Glonass) and the integration with other types of navigation sensors.

Learning Objectives

  • explain the role of space-, ground- and user segments of Global Navigation Satellite Systems
  • explain the components of GNSS receivers and the fundamentals of code- and carrier tracking
  • analyze baseband processing algorithms using a GNSS software receiver
  • formulate a nonlinear least squares adjustment algorithm for position estimation
  • analyze GNSS error-sources, such as ionospheric delay, tropospheric delay and multipath
  • apply filtering techniques in GNSS for more reliable estimations
  • describe other navigation sensors and strategies for integration with GNSS to improve the robustness and solution availability
  • review relative carrier phase position methods for precise positioning applications
  • apply the RINEX file format to exchange of GNSS measurement and satellite ephemeris parameters

Course Content

The basis for the course is to provide the knowledge necessary to develop the methodologies for GNSS data processing for enhanced positioning and navigation.

The course exercises are based on the implementation of a number of routines and models often used in practice. The lectures support the exercises and provide the necessary mathematical background.

The following subjects will be dealt with: computation of positions from pseudoranges and carrier phase data, modelling of clock errors and atmospheric effects, computation of DOP-values, transformation of positions and covariances. Furthermore, examples of the use of Kalman filtering for GNSS positioning are discussed, including the challenges related resolution of ambiguities.

Exercises are carried out using Matlab.

Recommended prerequisites

Teaching Method

Lectures and exercises


See course in the course database.





13 weeks




DTU Lyngby Campus

Course code 30554
Course type Candidate
Semester start Week 5
Semester end Week 19
Days Thurs 8-12

7.500,00 DKK