3 ECTS credits
90 h study time
Offer 1 with catalog number 4019818ENR for all students in the 1st semester at a (E) Master - advanced level.
Partim L. Van Biesen - H. Sahli
This course aims to give students of engineering sciences a clear introduction into navigation, in the broadest sense and based on its historical development. This means that the basic knowledge of mathematical and geographical descriptions must be revised and that the theory of terrestrial navigation will be studied. Through practical examples of navigation the student is meant to become acquainted with the application of the concepts and theoretical findings. After having followed this course, students must be capable of proposing the methods required for positioning and dead reckoning, defining the uncertainties associated with it, and must be able to suggest position and movement sensors, indicate correction and processing algorithms, and will be able to analyse fusing methods and networking. When we discuss automatic navigation and intelligence emphasis is of course placed on road vehicles.
Rationale: (L. Van Biesen)
General introduction to automatic navigation. Short historical perspective. Introduction to geodesion and map projection systems used in navigation (Latitude and Longitude. Motivation for nautical mile and knots. Mercator and Lambert projections. Reference ellipsoids and datum, WGS84).
Positioning techniques: (L. Van Biesen)
Short introduction (revision) of reproduction of radio waves (general electromagnetic reproduction, antennae, reproduction modes like ground wave, ionospherical reproduction, optical view). Measuring methods divided into 4 classes (angle directing methods, phase measurements, signal strength measurements, time measurements). Removing ambiguities (with GPS serving as an example), hyperbolic positioning methods. Localising through cellular networks (GSM, UMTS).
Satellite navigation: (L. Van Biesen)
Study of GPS and Differential GPS. GLONASS, Galileo and GPS-III.
Terrestrial navigation: (L. Van Biesen)
Problems with the use of satellite positioning and cellular radio in urban areas (urban canyon navigation). Methods and sensors for estimation of positioning and dead reckoning (ABS, gyroscopes, accelerometers).
Intelligent vehicles (H. Sahli)
Image processing, line tracking, traffic control, positioning, anti-collision,...
Description tutoring: after class, by appointment or via e-mail.
This course contributes to the following programme outcomes of the Master in Applied Computer Sciences:
MA_A: Knowledge oriented competence
4. The Master in Engineering Sciences can reformulate complex engineering problems in order to solve them (simplifying assumptions, reducing complexity)
MA_B: Attitude
12. The Master in Engineering Sciences has a creative, problem-solving, result-driven and evidence-based attitude, aiming at innovation and applicability in industry and society
14. The Master in Engineering Sciences has consciousness of the ethical, social, environmental and economic context of his/her work and strives for sustainable solutions to engineering problems including safety and quality assurance aspects
MA_C: Specific competence
17.The Master in Applied Computer Sciences has a thorough understanding of the underlying physical principles and the functioning of electronic and photonic devices, of sensors and actuators and is able to use them to conceive information processing systems and more specifically systems of systems
19.The Master in Applied Computer Sciences has knowledge of and is able to use advanced processing methods and tools for the analysis of (big) data in different application domains
20.The Master in Applied Computer Sciences is able to design (distributed) systems of systems and execute performance assessment of the designed product
22.The Master in Applied Computer Sciences has a thorough knowledge of hardware platforms, operating systems, firmware and their impact on smart systems of systems
23.The Master in Applied Computer Sciences is aware of data privacy and security aspects
26. The Master in Applied Computer Sciences can apply his/her acquired knowledge and skills for designing smart city or digital health dedicated systems of systems.
27. The Master in Applied Computer Sciences is aware of and critical about the impact of ICT on society.
The final grade is composed based on the following categories:
Other Exam determines 100% of the final mark.
Within the Other Exam category, the following assignments need to be completed:
Not applicable
This offer is part of the following study plans:
Master in Applied Sciences and Engineering: Applied Computer Science: Standaard traject