English

Kalman-Bucy filtering and minimum mean square estimator under uncertainty

Optimization and Control 2020-11-09 v3 Probability

Abstract

In this paper, we study a generalized Kalman-Bucy filtering problem under uncertainty. The drift uncertainty for both signal process and observation process is considered and the attitude to uncertainty is characterized by a convex operator (convex risk measure). The optimal filter or the minimum mean square estimator (MMSE) is calculated by solving the minimum mean square estimation problem under a convex operator. In the first part of this paper, this estimation problem is studied under g-expectation which is a special convex operator. For this case, we prove that there exists a worst-case prior. Based on this worst-case prior we obtained the Kalman-Bucy filtering equation under g-expectation. In the second part of this paper, we study the minimum mean square estimation problem under general convex operators. The existence and uniqueness results of the MMSE are deduced.

Keywords

Cite

@article{arxiv.2004.09202,
  title  = {Kalman-Bucy filtering and minimum mean square estimator under uncertainty},
  author = {Shaolin Ji and Chuiliu Kong and Chuanfeng Sun and Ji-Feng Zhang},
  journal= {arXiv preprint arXiv:2004.09202},
  year   = {2020}
}

Comments

24 pages

R2 v1 2026-06-23T14:57:48.062Z