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arXiv · 2206.06784

Stochastic Event-triggered Variational Bayesian Filtering

Xiaoxu Lv·Peihu Duan·Zhisheng Duan·Guanrong Chen·Ling Shi
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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.

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BibTeXRIS

Xiaoxu Lv, Peihu Duan, Zhisheng Duan, Guanrong Chen, Ling Shi. 2022-06-14. Stochastic Event-triggered Variational Bayesian Filtering. https://arxiv.org/abs/2206.06784

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