New approach to information fusion steady-state Kalman filtering

In recent years, a compelling need has arisen to understand the effects of distributed information structures on estimation and filtering. In this study, a bibliographical review on distributed Kalman filtering (DKF) is provided. The study contains a classification of different approaches and methods involved to DKF. The applications of DKF are also discussed and explained separately. A comparison of different approaches is briefly carried out. Focuses on the contemporary research are also addressed with emphasis on the practical applications of the techniques. An exhaustive list of publications, linked directly or indirectly to DKF in the open literature, is compiled to provide an overall picture of different developing aspects of this area.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-cta.2012.0732

Shu-Jun Liu

Papers

Optimal and self-tuning white noise estimators with applications to deconvolution and filtering problems