Course detail

Analysis of Measuring Data

FAST-IE52Acad. year: 2019/2020

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.

Department

Institute of Geodesy (GED)

Learning outcomes of the course unit

Not applicable.

Prerequisites

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

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

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

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Not applicable.

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

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.

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.

Specification of controlled education, way of implementation and compensation for absences

Extent and forms are specified by guarantor’s regulation updated for every academic year.

Classification of course in study plans

  • Programme D-P-C-GK Doctoral

    branch GAK , 1. year of study, winter semester, 8 credits, elective

  • Programme D-K-C-GK Doctoral

    branch GAK , 1. year of study, winter semester, 8 credits, elective

Type of course unit

 

Lecture

39 hours, optionally

Teacher / Lecturer

eLearning