Course - Nonlinear State Estimation - TK8102
TK8102 - Nonlinear State Estimation
About
Lessons are not given in the academic year 2024/2025
Course content
The course is given spring in even-numbered years. The course presents state estimation techniques for nonlinear dynamic systems with an additional focus on Multiple Target Tracking (MTT) and Simultaneous Localization And Mapping (SLAM) methods, the underlying theoretic foundations and implementation skills. The course is given in English.
Learning outcome
KNOWLEDGE: * A thorough knowledge of theory and methods for state estimation of deterministic and stochastic nonlinear dynamical systems * Relevant definitions and properties of observability * State estimation techniques: Filtering and smoothing * Kalman-based techniques for stochastic systems* Nonlinear observers * Graphical models, Factor-graph based SLAM techniques * Parameter estimation * Data association * Applications in sensor fusion SKILLS: * Proficiency in analyzing the observability properties of nonlinear dynamical systems * Proficiency in independently assessing the advantages and disadvantages of different estimation methods, and make a qualified choice of method for a given system * Proficiency in independently applying the different methods for estimator design * Proficiency in designing SLAM systems. GENERAL COMPETENCE: * Skills in applying this knowledge and proficiency in new areas and complete advanced tasks and projects * Skills in communicating extensive independent work, and master the technical terms of nonlinear state estimation * Ability to contribute to innovative thinking and innovation processes
Learning methods and activities
Study groups and optional problem sets. Project with report.
Recommended previous knowledge
Knowledge of observers, Kalman filter, statistics and stochastic processes. TTK4250 Sensor Fusion or TTK4150 Nonlinear Systems can be useful.
Required previous knowledge
TTK4115 Linear Systems Theory or a similar course that covers Kalman filter, stochastic system theory and estimation.
Course materials
A collection of papers, which will be given at the beginning of the semester.
No
Version: 1
Credits:
7.5 SP
Study level: Doctoral degree level
No
Language of instruction: English
Location: Trondheim
- Engineering Cybernetics
Department with academic responsibility
Department of Engineering Cybernetics
Examination
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"