Dynamically Iterated Filters: A unified framework for improved iterated filtering and smoothing

A Kullberg, MA Skoglund, I Skog… - arXiv preprint arXiv …, 2024 - arxiv.org
Typical iterated filters, such as the iterated extended Kalman filter (IEKF), iterated unscented
Kalman filter (IUKF), and iterated posterior linearization filter (IPLF), have been developed to …

Unified Linearization-based Nonlinear Filtering

A Kullberg, I Skog, G Hendeby - arXiv preprint arXiv:2309.07631, 2023 - arxiv.org
This letter shows that the following three classes of recursive state estimation filters:
standard filters, such as the extended Kalman filter; iterated filters, such as the iterated …

Dynamic rEvolution: Adaptive state estimation via Gaussian processes and iterative filtering

A Kullberg - 2024 - diva-portal.org
For virtually every area of science and engineering, state estimation is ubiquitous. Accurate
state estimation requires a moderately precise mathematical model of the system, typically …

Modern Bayesian Object Tracking: Challenges and Solutions

Q Li - 2023 - repository.cam.ac.uk
Target tracking is a challenging problem with a wide range of applications such as
surveillance, robotics, and autonomous vehicles. Recent years have seen significant …