Next admission period opens February 2018
Many satellite applications require extremely accurate positioning of the satellite in order to be able to interpret the data. For example, measuring the height of the oceans and ice sheets and positioning of tectonic plates requires knowing the position of the satellite with centimetre-level accuracy. Reaching this accuracy for a satellite that flies at 500 km altitude with velocities around 7 km/s is a great challenge. This challenge, also known as "Precise Orbit Determination (POD)", will be addressed in this course. In the course, you will learn techniques such as least squares estimation, and Kalman filtering which is widely used statistical techniques for estimating parameters from observations. Concepts such as reference frames, atmospheric refraction and relativity will also be addressed. During the lectures and assignments, you will be introduced to the various ground and space-based tracking systems, including satellite laser ranging, Doppler tracking, and GPS positioning. The course will provide you with several assignments in order to practice the statistical techniques used in satellite orbit determination. Shooting problems in relation to parameter estimation as applied during this course can be used in a variety of engineering and scientific applications. You will be able to process large datasets acquired by satellite systems or other instruments and estimate parameters in a dynamic model. On completion of this course you will be able to:
- Process real-world satellite tracking data.
- Estimate satellite orbit and dynamic parameters from satellite tracking data.
- Understand the scientific applications of satellite orbit determination.
Week 1: Introduction to statistics In this week we will introduce basic statistical tools that you will need for the rest of the course. Concepts such as variance, covariance, and correlation will be discussed. In practice exercises, these concepts will be applied to observation data. For the homework assignment in this week, you will use range-rate data from the TU Delft tracking station. Week 2: Satellite Observations You will learn about the different measurements techniques and observations models for determining the orbit of the satellite. The theory will be about observations to/from satellites, light-time, refraction, relativity. In the end, you will be able to identify and discuss the different observations techniques. Week 3: Introduction to satellite navigation During this week we will dedicate the course to Global Navigation Satellite System techniques. We will discuss the GPS observation system and its uncertainties. Furthermore, this week will be about linearization of the dynamic and observation models. This weeks assignment will be about the GPS navigation solution of the SWARM orbit. Week 4: Reference Systems Reference systems are the main element in satellite orbit determination. This week we will discuss the different reference systems used in satellite orbit determination. The lecture discusses the relation between time systems, coordinate systems, potential fields, Earth rotation, precession, nutation and polar motion. Week 5: Statistics continued Because of the importance of your knowledge about statistical data handling, we will discuss more theory this week. Elements of statistics are discussed with respect to constraint equations, linear dependency, and implementation of algorithms. For the assignment this week the GPS solution of the previous assignment is used and you will determine some parameters of the orbit and observational models used. Week 6: Batch and sequential filtering This week the difference between batch and sequential filtering will be shown. Furthermore, subjects like Kalman filtering, state vector, and covariance matrix will be elaborated. The assignment of this week will be about applying a Kalman Filter on the already used GPS navigation solution. Week 7: Applications The theory and exercises from the previous weeks can now be applied on real-world cases. In this week several applications of the theory are discussed and results of the modelling will be shown. We will guide you through the procedures applied during POD and the main results obtained for recent Earth Observation missions such as CryoSat-2 and GRACE.
- Cost: € 1000
- Course Length: 9 weeks
- Estimated Effort: 12 - 13 hours per week
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Last updated November 25, 2017