An interactive application that provides a simulation of the Kalman filter for high-precision aircraft navigation. This project demonstrates how the algorithm takes erratic, noisy sensor readings ...

A high-performance C++/Python library for blob detection using FFT-accelerated Laplacian of Gaussian convolution, with robust tracking via Hungarian algorithm matching and Kalman filter prediction.

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 ...

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 ...

Abstract: Kalman filtering, a recursive state estimation filter is a robust method for tracking objects. It has been proven that Kalman filter gives a good estimation when tested on various tracking ...

The space station is a bridgehead for human space exploration missions. During its construction, operation, and maintenance, there are a variety of tasks that need to be performed. However, the space ...

The use of Kalman filter methods for high-performance order tracking of noise and vibration signals was introduced in 1993. Based on experience with that original formulation, further work has ...

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 ...