548-0150/02 – Advanced methods in Localization and Navigation (PMLN)

Gurantor departmentDepartment of GeoinformaticsCredits4
Subject guarantordoc. Ing. Michal Kačmařík, Ph.D.Subject version guarantordoc. Ing. Michal Kačmařík, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Study languageEnglish
Year of introduction2021/2022Year of cancellation
Intended for the facultiesHGFIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
KAC072 doc. Ing. Michal Kačmařík, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 8+8

Subject aims expressed by acquired skills and competences

The student demonstrates knowledge of: - phenomena and errors affecting GNSS positioning, - GNSS techniques based on differenced and undifferenced observations, - long-term and short-term coordinate changes in time, - current techniques for positioning and navigation and the possibilities for combining them, - the available software in the area of study, The student can: - process data from various GNSS measurements using the Precise Point Positioning method and the double-difference method, - solve long-term routine GNSS processing in order to obtain time series of precise coordinates of receivers, - use standard mobile devices to apply advanced GNSS positioning techniques, - use standard mobile devices for positioning and navigation using a combination of location and navigation techniques (GNSS, inertial, using wireless networks)

Teaching methods



The course in the first part provides theoretical and practical knowledge of advanced techniques for positioning using Global Navigation Satellite Systems (GNSS). In the second part, it introduces students other existing sensors and techniques usable for localization and navigation in space and the possibility of their combinations.

Compulsory literature:

TEUNISSEN, P., MONTENBRUCK, O. Springer Handbook of Global Navigation Satellite Systems. Springer, 2017, ISBN: 978-3-030-73172-4. QUAN, W., LI, J., GONG, X., FANG, J.: INS/CNS/GNSS Integrated Navigation Technology. Springer, Berlin, Heidelberg, 2015. ISBN:978-3-662-45158-8. SUBIRANA, S., ZORNOZA, J., HERNANDÉZ-PAJARES, M.: GNSS DATA PROCESSING, Volume I: Fundamentals and Algorithms. European Space Agency, 2013. ISBN:978-92-9221-886-7. SAMAMA, N. Indoor positioning: technologies and performance. Wiley, 2019. ISBN:978-1-119-42184-9.

Recommended literature:

DACH, R., LUTZ, S., WALSER, P., FRIDEZ, P.: Bernese GNSS Software, Version 5.2. University of Bern, 2015, 884 str. ISBN:978-3-906813-05-9. BURGER, W., BURGE, M., J.: Principles of Digital Image Processing: Fundamental Techniques. Springer, 2011. ISBN:978-1848001909. SAND, S., DAMMANN, A., MENSING, Ch. Positioning in wireless communications systems. Wiley, 2014. ISBN:978-0-470-77064-1. YASUDA, Y., Martins, L.E., Cappabianco, F.: Autonomous Visual Navigation for Mobile Robots: A Systematic Literature Review. ACM Comput. Surv., 2020, 53, 1.

Way of continuous check of knowledge in the course of semester

Students are asked about knowledge from areas that they should have already known from previous lectures. They work on two individual tasks. Written and oral exam.


Other requirements

No additional requirements are imposed on the student.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1) Introduction to precise GNSS positioning 2) Observation and support data for precise GNSS positioning, their pre-processing 3) Phenomena and errors influencing GNSS positioning 4) Ambiguity resolution 5) Precise Point Positioning (PPP) technique 6) Double-differenced techniques, network solution 7) Work with coordinates, long-term and short-term changes in coordinates 8) Localization via wireless networks 9) Vision based localization and navigation 10) Inertial localization and navigation 11) Fusion of sensors and technologies 12) Indoor lokalizace a navigace 13) Simultaneous navigation and mapping (SLAM)

Conditions for subject completion

Full-time form (validity from: 2021/2022 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 33  17
        Examination Examination 67  34 3
Mandatory attendence participation: Attend at least 80 % of classes.

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Conditions for subject completion and attendance at the exercises within ISP: Lectures in the form of self-study of materials assigned by the lecturer. Possibility of personal or on-line consultation. Participation in exercises according to the student's capabilities. In order to receive credit, student must complete two assignments no later than at the end of the examination period of the semester. The assignments will be provided by lecturer leading exercices. Examination must be taken in person.

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2024/2025 (N0532A330044) Geoinformatics GIT P English Ostrava 2 Compulsory study plan
2023/2024 (N0532A330044) Geoinformatics GIT P English Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction

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