A Framework for Nonlinear Filtering in MATLAB
Independent thesis Basic level (professional degree), 20 points / 30 hpStudent thesis
The object of this thesis is to provide a MATLAB framework for nonlinear filtering in general, and particle filtering in particular. This is done by using the object-oriented programming paradigm, resulting in truly expandable code. Three types of discrete and nonlinear state-space models are supported by default, as well as three filter algorithms: the Extended Kalman Filter and the SIS and SIR particle filters. Symbolic expressions are differentiated automatically, which allows for comfortable EKF filtering. A graphical user interface is also provided to make the process of filtering even more convenient. By implementing a specified interface, programming new classes for use within the framework is easy and guidelines for this are presented.
Place, publisher, year, edition, pages
Institutionen för systemteknik , 2005. , 164 p.
Nonlinear Filtering, Particle Filters, EKF, MATLAB
IdentifiersURN: urn:nbn:se:liu:diva-5190ISRN: LiTH-ISY-EX--05/3733--SEOAI: oai:DiVA.org:liu-5190DiVA: diva2:21103