Master Thesis on Adaptive Kalman Filtering for Precise Orbit Determination of Low Earth Satellites (d/f/m)

工作内容

Job Description

Are you looking for a Master Thesis? Would you like to work on cutting edge Guidance/Navigation/Control (GNC) system design with focus on Adaptive Kalman Filtering for Precise Orbit Determination?

Then apply now! We look forward to you joining us.

Location: Friedrichshafen @ Lake Constance

Start: August 2022

Duration: 6 months

Department

The AOCS, GNC & Flight Dynamics department is the center of competence in Airbus for attitude and orbit control systems (AOCS), Guidance/Navigation/Control (GNC), flight dynamics, and control engineering for all kinds of spacecraft. This includes among others modelling, design, synthesis, and verification & validation of the AOCS/GNC systems.

As a Master Student You Will Learn About

Precise Orbit Determination, nonlinear filtering/estimation, satellite dynamics and modelling, C++, object-oriented programming, being part of an international work environment.

Thesis Topic

Earth observation satellite missions require precise knowledge of the instrument’s orbit to produce high quality data. This orbit is usually determined by means of GNSS-based Precise Orbit Determination (POD). Within the department, a new POD-Software written in C++ is under development. In the scope of this development, new methods and algorithms to improve POD capabilities are being continuously implemented and evaluated.

One of the approaches to perform parameter and dynamical state estimation within the POD can be based on the Extended Kalman Filter. In this case, determining the noise characteristics of the system dynamics and measurements comes with a number of challenges. Lengthy tuning and a good knowledge of the dynamic environment might be necessary to optimize the orbit determination performance. Adaptive Kalman Filtering can estimate the system’s noise characteristics based on observations and can potentially improve the filter’s performance. Within this thesis, a fitting Adaptive Kalman Filter algorithm should be identified and implemented in the existing POD-Software. The performance of the newly implemented algorithm should further be investigated and compared to existing methods.

Tasks

• Familiarization with POD and existing POD-Software written in modern C++
• Development of an Adaptive Kalman Filter algorithm for POD of LEO satellites
• Implementation of the Adaptive Kalman Filter within the software
• Performance analysis
• Documentation of work
  
  

Qualifications

• Enrolled as fulltime student (m/f/d) in Aerospace Engineering, Geodesy or similar field of study
• Very good knowledge of C++ or other programming language
• Skills related to optimal estimation/filtering (Kalman Filter, Least Squares Adjustment etc.)
• Knowledge about orbit determination
• English is mandatory
• German would be an asset
  
  

You are a good team player, have excellent communication skills, and are able to work independently.

Contact

Does this job description fit your objectives and profile? Take the next step in your career and come and join us!

How To Apply

Online via https://www.airbus.com/careers.html

Reference number JR10132575

Please provide the following documents:cover letter, C.V., relevant certificates, current certificate of enrolment

You can direct your cover letter to: Maddalena Brielmayer

Should you have general questions regarding this position you can write an E-Mail to: myapplication@airbus.com

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company

Airbus Defence and Space GmbH

Contract Type

Final-year Thesis / Stage fin d’étude / Abschlussarbeit / Proyecto fin de carrera

Experience Level

Student / Etudiant / Student / Estudiante

Job Family

Vehicle Mission & Control

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