A real-time Python simulation of a 2D object tracked using noisy radar measurements and a Kalman Filter for state estimation. This project demonstrates how noisy sensor data can be filtered to ...

Kalman and Bayesian Filters in Python Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Jupyter Notebook so that you can run and ...

Kalman filters have long stood as a cornerstone in the field of target tracking and state estimation, providing an optimally recursive solution for estimating the state of dynamic systems in the ...

Abstract: This paper proposes a novel algorithm, the Kalman Filter Embedded Trust Region (KFETR), for target tracking. Kalman filter and trust region are two successful methods for object tracking.

Abstract: In this paper, we address the problem of tracking dynamic changes in graph topology under a linear graph filtering random process. We propose a graph-based state-space model (SSM), where the ...

As a follow-on course to "Kalman Filter Boot Camp", this course derives the steps of the linear Kalman filter to give understanding regarding how to adjust the method to applications that violate the ...