arXiv Open Access 2025

A Robust State Filter Against Unmodeled Process And Measurement Noise

Weitao Liu

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Abstrak

This paper introduces a novel Kalman filter framework designed to achieve robust state estimation under both process and measurement noise. Inspired by the Weighted Observation Likelihood Filter (WoLF), which provides robustness against measurement outliers, we applied generalized Bayesian approach to build a framework considering both process and measurement noise outliers.

Topik & Kata Kunci

stat.ML cs.LG

Penulis (1)

Weitao Liu

Format Sitasi

APA MLA BibTeX

Liu, W. (2025). A Robust State Filter Against Unmodeled Process And Measurement Noise. https://arxiv.org/abs/2511.19157

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Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓