# 2020/2021

## Prerequisite/Recommended prerequisite for participation in the module

Numerical methods, probability, statistics and stochastic processes.

## Content, progress and pedagogy of the module

Purpose

• to contribute to studentsâ€™ attainment of knowledge and comprehension of Kalman filter theory.
• to contribute to studentsâ€™ attainment of knowledge and comprehension of how to apply Kalman filter theory for engineering problems, such as abnormal diagnosis and multiple target tracking etc.

Content

Conventional Kalman filter theory:

• Scale Kalman filter
• Vector-based Kalman filter
• Convergence and preconditions

Extended Kalman filter theory:

• Extended Kalman filter (EKF)
• Uncended Kalman filter (UKF)
• Multi-mode Kalman filter

Application of KF theory

• Fault detection using KF theory
• Fault diagnosis using KF theory
• Multiple target tracking
• Multi-mode system estimation

### Learning objectives

#### Knowledge

• Have knowledge and comprehension for Kalman filter theory
• Have knowledge and comprehension for extended Kalman filter techniques
• Have knowledge and comprehension for vector-based Kalman filter theory.
• Have comprehension of the application of Kalman filter theory to abnormal scenario diagnosis
• Have comprehension of the application of Kalman filter theory to multiple target tracking

#### Skills

• Be able to apply Kalman filter theory for state estimation problem in the presence of noises.
• Be able to apply Kalman filter theory for abnormal diagnosis problem
• Be able to apply Kalman filter theory for multiple target tracking problem
• Be able to judge the usefulness of the set up methods
• Be able to relate the methods to applications in the industry

#### Competences

• Independently be able to define and analyze scientific problems using Kalman filter theory
• Independently be able to apply Kalman filter theory for different engineering problems

### Type of instruction

The program is based on a combination of academic, problem-oriented and interdisciplinary approaches and organized based on the following work and evaluation methods that combine skills and reflection:

• Lectures
• Classroom instruction
• Project work
• Workshops
• Exercises (individually and in groups)
• Teacher feedback
• Reflection
• Portfolio work

Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student

## Exam

### Exams

 Name of exam Kalman Filter Theory and its Application Type of exam Written or oral exam ECTS 5 Assessment 7-point grading scale Type of grading Internal examination Criteria of assessment The criteria of assessment are stated in the Examination Policies and Procedures