Work

A Student's t filter for heavy tailed process and measurement noise

Year: 2013

Type: conference-paper

Abstract: We consider the filtering problem in linear state space models with heavy tailed process and measurement noise. Our work is based on Student's t distribution, for which we give a number of useful results. The derived filtering algorithm is a generalization of the ubiquitous Kalman filter, and reduces to it as special case. Both Kalman filter and the new algorithm are compared on a challenging tracking example where a maneuvering target is observed in clutter.

Source: IEEE International Conference on Acoustics Speech and Signal Processing

DOI: 10.1109/icassp.2013.6638770

Authors: Michael Roth, Emre Ozkan, Fredrik Gustafsson

Institution: Linköping University

Language: English

Topic: Target Tracking and Data Fusion in Sensor Networks

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2062100941

FWCI: 2.24

Cites: 24

Cited by: 259

Related to: 10