Course Details

Analysis of Measuring Data

Academic Year 2024/25

IE52 course is part of 1 study plan

​ D-K-C-GK / GAK Winter Semester 1st year

Planning of experimentsMultidimensional quantities and their characteristics. Accuracy measures and their meaning. Testing and analysis of measurement results and values entering the adjustment process. Physical and mathematical correlation. Partial and multi-dimensional correlation. Matrix of correlation coefficients, covariance matrix. Systematical errors. Laws of error propagation. Errors of composite functions. Analysis of error limits. Adjustment of correlated measurements. Block adjustment. Collocation. Kalman filter. Robust adjustment methods. Analysis of covariance and weight matrixes. Planning of experiments, optimization methods. Design of methodology and technology for complex accuracy evaluation in doctor thesis.

Credits

8 credits

Language of instruction

Czech

Semester

winter

Course Guarantor

doc. Ing. Josef Weigel, CSc.

Institute

Institute of Geodesy

Forms and criteria of assessment

examination

Entry Knowledge

Methods of mathematical and statistical analysis. Fundamentals of data analysis and adjustment.

Aims

Mastering of methods for analysis and testing of measuring results. Understanding of correlations and their treatment in adjustment process. Understanding of principles of collocation, Kalman data filtering, and robust adjustment methods. Getting an overview of methods of experimental planning and optimization.

Basic Literature

Borradaile, G.: Statistics for Earth Science Data. Springer Verlag 2003
Teunissen, P.J.G.: Testing Theory - an Introduction. Delft University Press 2002

Offered to foreign students

Not to offer

Course on BUT site

https://www.vut.cz/en/students/courses/detail/283148

Lecture

13 weeks, 3 hours/week, elective

Syllabus

1. Multidimensional quantities. Accuracy measures. 2. Testing and analysis of measurements results. Physical and mathematical correlation. Testing of inputs of adjustment process. 3. Systematical errors. Laws of error propagation. Errors of composite functions. 4. Matrix of correlation coefficients, covariance matrix. Adjustment of correlated measurements. Block adjustment. 5. Collocation. Kalman filter. Robust adjustment. Analysis of covariance and weight matrixes. 6. Planning of experiments. Optimization methods.