Bibliographic Details
| Title: |
Stochastic Event-triggered Variational Bayesian Filtering |
| Authors: |
Lv, Xiaoxu, Duan, Peihu, Duan, Zhisheng, Chen, Guanrong, Shi, Ling |
| Publication Year: |
2022 |
| Collection: |
Computer Science |
| Subject Terms: |
Electrical Engineering and Systems Science - Signal Processing, Electrical Engineering and Systems Science - Systems and Control |
| More Details: |
This paper proposes an event-triggered variational Bayesian filter for remote state estimation with unknown and time-varying noise covariances. After presetting multiple nominal process noise covariances and an initial measurement noise covariance, a variational Bayesian method and a fixed-point iteration method are utilized to jointly estimate the posterior state vector and the unknown noise covariances under a stochastic event-triggered mechanism. The proposed algorithm ensures low communication loads and excellent estimation performances for a wide range of unknown noise covariances. Finally, the performance of the proposed algorithm is demonstrated by tracking simulations of a vehicle. |
| Document Type: |
Working Paper |
| Access URL: |
http://arxiv.org/abs/2206.06784 |
| Accession Number: |
edsarx.2206.06784 |
| Database: |
arXiv |
