Open AccessGeneralized LMMSE Filtering with Out‐of‐Sequence Observations in Arbitrary Constant Delay
Author(s) -
Lei Ming,
Baehr Christophe,
Jing Zhongliang
Publication year - 2019
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2019.08.005
Subject(s) - sequence (biology) , filter (signal processing) , generalization , constant (computer programming) , minimum mean square error , mathematics , state (computer science) , control theory (sociology) , algorithm , kalman filter , computer science , filtering problem , filter design , statistics , mathematical analysis , artificial intelligence , genetics , control (management) , estimator , computer vision , biology , programming language
Focusing on the problem of state estimation in the presence of sensor faults and Out‐of‐sequence measurement (OOSM) observations synchronously, we derive a formulation of Linear minimum mean squared error (LMMSE) filter with the arbitrary time delay of OOSM, the generalization of the present work lies in simultaneous treatment of correlated faults together with OOSMs that arrive at an arbitrary delay in a linear‐optimal manner. The approach is demonstrated in a numerical comparison.