Optimization of Covariance Matrices of Kalman Filter with Unknown Input Using Modified Directional Bat Algorithm
The proper selection of the model error covariance matrix and the measurement noise covariance matrix of Kalman filter is an optimization problem. Some scholars have studied this, but there is relatively little research on the selection of the two covariance matrices for Kalman filters with an unkno...
Saved in:
Main Authors: | Lijun Liu, Chang Yin, Yonghui Su, Yinghai Lin, Ying Lei |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Buildings |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-5309/15/2/196 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive Kalman Filtering: Measurement and Process Noise Covariance Estimation Using Kalman Smoothing
by: Theresa Kruse, et al.
Published: (2025-01-01) -
Robust strong tracking unscented Kalman filter for non‐linear systems with unknown inputs
by: Xinghua Liu, et al.
Published: (2022-05-01) -
Estimating Complex Signals With a Fuzzy-Enhanced Kalman Filter: A Note on “the Output Regulation and the Kalman Filter as the Signal Generator”
by: Jesus Alberto Meda-Campana, et al.
Published: (2025-01-01) -
Positioning accuracy improvement in high‐speed GPS receivers using sequential extended Kalman filter
by: Narges Rahemi, et al.
Published: (2021-06-01) -
A comparison of nonlinear filtering approaches in the context of anHIV model
by: H. Thomas Banks, et al.
Published: (2010-03-01)