Year: 2019
Type: conference-paper
Abstract: This paper suggests a few novel Cholesky-based square-root algorithms for the maximum correntropy criterion Kalman filtering. In contrast to the previously obtained results, new algorithms are developed in the so-called condensed form that corresponds to the a priori filtering. Square-root filter implementations are known to possess a better conditioning and improved numerical robustness when solving ill-conditioned estimation problems. Additionally, the new algorithms permit easier propagation of the state estimate and do not require a back-substitution for computing the estimate. Performance of novel filtering methods is examined by using a fourth order benchmark navigation system example.
Author: Maria V. Kulikova
Institutions: University of Lisbon, Instituto Superior Técnico
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2982479689