About this document
Adaptive Kalman Filter with Noise Update by Andrew Fong is a document available to read on EtoBox.
This document describes an improved adaptive Kalman filter (AKF) with recursive rules for updating the process and observation noise covariance matrices. The AKF aims to estimate states more accurately when the noise statistics are unknown or uncertain. It derives two recursive rules for adapting the covariance matrices based on covariance matching principles. Testing shows the AKF estimates states more precisely with less noise and is more stable than the conventional Kalman filter when the initial covaria
- Author
- Andrew Fong
- Language
- EN