Data fusion in networks is often organized in the presence of correlated noise that also must be addressed in the design. Wireless communication channels often deliver information at a receiver with time‐stamped or randomly delayed and missing data that requires advanced modeling and modified estimators. This chapter looks at several such advanced topics and discusses the corresponding finite impulse response (FIR) solutions and demonstrates the better robustness of FIR state estimator. Information fusion in wireless sensor network is one of the key problems the effective solution of which justifies the network design. The design of hybrid structures refers to extreme properties of linear state estimators: the Kalman Filter is optimal but not robust, and the Unbiased finite impulse response filter is robust but not optimal. Combining optimal and robust estimators in hybrid structures gives the best compromise between accuracy and robustness, and optimal fusion can be organized in different ways.
Advanced Topics in FIR State Estimation
Optimal and Robust State Estimation ; 359-388
2022-08-09
30 pages
Article/Chapter (Book)
Electronic Resource
English
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