Stochastic Event-triggered Variational Bayesian Filtering

Xiaoxu Lv; Peihu Duan; Zhisheng Duan; Guanrong Chen; Ling Shi

Stochastic Event-triggered Variational Bayesian Filtering

Signal Processing 2022-06-15 v1 Systems and Control Systems and Control

Authors: Xiaoxu Lv , Peihu Duan , Zhisheng Duan , Guanrong Chen , Ling Shi

Abstract

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.

Keywords

parameter estimation signal processing kalman filtering

Cite

@article{arxiv.2206.06784,
  title  = {Stochastic Event-triggered Variational Bayesian Filtering},
  author = {Xiaoxu Lv and Peihu Duan and Zhisheng Duan and Guanrong Chen and Ling Shi},
  journal= {arXiv preprint arXiv:2206.06784},
  year   = {2022}
}

Stochastic Event-triggered Variational Bayesian Filtering

Abstract

Keywords

Cite

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