One-step condensed forms for square-root maximum correntropy criterion Kalman filtering
Optimization and Control
2023-10-31 v1 Computational Engineering, Finance, and Science
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 {\it condensed} form that corresponds to the {\it 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.
Cite
@article{arxiv.2310.18750,
title = {One-step condensed forms for square-root maximum correntropy criterion Kalman filtering},
author = {Maria Kulikova},
journal= {arXiv preprint arXiv:2310.18750},
year = {2023}
}