Stochastic Event-triggered Variational Bayesian Filtering

Autor:	Lv, Xiaoxu, Duan, Peihu, Duan, Zhisheng, Chen, Guanrong, Shi, Ling
Rok vydání:	2022
Předmět:	Electrical Engineering and Systems Science - Signal Processing Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	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.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2206.06784 Zobrazit plný text záznamu View this record from Arxiv