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| JDZ7214 | Kalman Filtering and Smoothing in Geodesy | 3+0+0 | ECTS:7.5 | | Year / Semester | Fall Semester | | Level of Course | Third Cycle | | Status | Elective | | Department | DEPARTMENT of GEOMATICS ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Mualla YALÇINKAYA | | Co-Lecturer | Prof. Dr. Mualla YALÇINKAYA | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | Analysing of geodetic problems by Kalman Filtering method. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | learn the concepts of prediction, filtering and smoothing. | 7 | 1, | | PO - 2 : | learn the applications of Kalman Filter in geodetic problems. | 7 | 1, | | PO - 3 : | learn studying of the results of Kalman Filter and LSQ. | 7 | 1, | | PO - 4 : | learn evaluating the results of Kalman Filter and LSQ together. | 7 | 1, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Prediction, filtering and smoothing. Linear filtering and smoothing. Non-linear approaches. Applying constant interval approaches to geodetic problems. Kalman Filtering method, accuracy analysis and applying to geodetic problems. Comparing Kalman Filtering and LSQ results and approaches for the combined adjustment of them. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Entrance; measurement and measurement concepts | | | Week 2 | Features of measurements | | | Week 3 | Statistical Distributions, Hypothesis Tests and Application | | | Week 4 | Methods and application to determine whether the data is normally distributed or not | | | Week 5 | Methods and application to determine whether the data is normally distributed or not | | | Week 6 | Adjustment geodetic data with the Least Squares Method | | | Week 7 | Elimination of incompatible measurements using the classical method | | | Week 8 | Robust estimation method | | | Week 9 | Mid-term exam | | | Week 10 | History of prediction theories; Kalman Filtering technique and its application areas, HOMEWORK | | | Week 11 | Kalman Filtering and Smoothing in Geodesy | | | Week 12 | Kalman-Filtering technique steps | | | Week 13 | Application of Kalman-Filtering technique in the initial period | | | Week 14 | Applications of Kalman-Filtering technique to geodesic problems | | | Week 15 | Assignment Presentations | | | Week 16 | End-of-term exam | | | |
| 1 | Grewal, M. S., Andrews, A. P., 1993, Kalman Filtering Theory and Practice, Printice Hall, Englewood Cliffs, New Jersey. | | | |
| 1 | Yalçınkaya (Ünver), M., 1994, Düşey Yöndeki Yerkabuğu Deformasyonlarının Kinematik Model İle Belirlenmesi, Doktora Tezi, K.T.Ü., Fen Bilimleri Enstitüsü, Trabzon. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 1 | 30 | | Homework/Assignment/Term-paper | 14 | | | 20 | | End-of-term exam | 16 | | 2 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Sınıf dışı çalışma | 6 | 14 | 84 | | Ödev | 6 | 3 | 18 | | Total work load | | | 102 |
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