"Kalman and Bayesian Filters in Python" looks amazing! ... your book is just what I needed - Allen Downey, Professor and O'Reilly author. Thanks for all your work on publishing your introductory text ...

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 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 ...

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 ...

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 ...

Abstract: To overcome the accuracy degradation for bearings-only tracking (BOT) under time-varying, unknown process noise, the adaptive square-root continuous-discrete extended Kalman filter (CD-EKF) ...

The final, formatted version of the article will be published soon. Due to the complex and ever-changing maritime environment, ships heavily rely on stable and reliable navigation systems during their ...