FC21212 Adjustment Computations
Course Outline
|
Course |
: FC 21212 – Adjustment Computations |
|
Core/Specialization |
: Core |
|
Programme |
: Bachelor of Science Honors in Surveying Sciences |
|
Department |
: Surveying & Geodesy |
|
Faculty |
: Faculty of Geomatics |
|
Contact Hours |
: 100 |
|
Year |
: II |
|
Semester |
: I |
|
Lecturer |
: |
|
Room No. |
: |
|
Telephone No. |
: +94 45 3453009 |
|
|
: |
Synopsis
The main goal of this course is to convey the knowledge necessary to perform an optimal adjustment of redundant data. In order to keep mathematical derivations brief and elegant, matrix notations have been used exclusively throughout the course. To help for better understand the theoretical concepts, a number of numerical examples (mostly originating from Geodesy and Surveying) are provided. Some parts of the content must be used for the techniques in “Students Centered Learning” system.
Contents
- Type of errors & error propagation
- Optimal estimation
- Least Square Adjustment
- Detection of Gross & Systematic Errors
Learning Outcomes
|
By the end of the course, students should be able to: |
|||
|
No. |
Course Learning Outcome |
Programme Outcome |
Assessment Methods |
|
1. |
Describe type of errors and their propagation in linear and non – linear functions |
P01 |
Assignment / Final Exam |
|
2. |
Describe optimal estimation by least square, maximum likelihood, and minimum error variance estimation methods |
P01 |
Assignment / Final Exam |
|
3. |
Describe condition and observation equation methods for an adjustment in linear and non – linear models |
P01 & P02 |
Assignment / Final Exam |
|
4. |
Explain iteration of observation equations for obtaining the final adjusted solution |
P01 & P02 |
Assignment / Final Exam |
|
5. |
Define & describe the detection of gross and systematic errors |
P01 & P02 |
Assignment / Final Exam |
Student Learning Time (SLT)
|
Teaching and Learning Activities |
Student Learning Time (hours) |
|
Direct Learning |
|
|
Lectures and Student Centered Learning (SCL) |
25 |
|
Independent Learning |
|
|
Preparation - Student Centred Learning activities |
28 |
|
Self-Learning (Library & Internet) |
25 |
|
Revision |
15 |
|
Assessment |
|
|
Assignments |
05 |
|
Final Examination(written) |
02 |
|
TOTAL (SLT) |
100 |
Teaching Methodology |
|
|
Lectures, and individual and group assignments |
|
References
- P. J. G. Teunissen, Adjustment Theory an Introduction, VSSD, Leeghwaterstraat 42, 2628 CA Delft, The Netherlands, 2006
- Huaan Fan, Theory of Errors and Least Squares Adjustment, Royal Institute of Technology (KTH), Division of Geodesy and Geoinformatics, 100 44 Stockholm, Sweden, August 2010
- C. D. Ghilani and P. R. Wolf, Adjustment Computations: Spatial Data Analysis, Fourth Edition. © 2006 John Wiley & Sons, Inc. ISBN: 978-0-471-69728-2
- Nico Sneeuw, Friedhelm Krumm, Adjustment Theory Lecture Notes, Geodätisches Institut, Universität Stuttgart, 2010
Grading
|
Assignment (x5) |
50% |
|
Final Examination |
50% |
|
Total |
100% |