Robust Kalman Filtering for 2-D Systems with Multiplicative Noises and Measurement Degradations

2021 ◽  
pp. 49-72
Author(s):  
Jinling Liang ◽  
Zidong Wang ◽  
Fan Wang
Keyword(s):  
Kalman Filtering ◽  
Multiplicative Noises

scholarly journals Kalman Filtering for Discrete Stochastic Systems with Multiplicative Noises and Random Two-Step Sensor Delays

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Dongyan Chen ◽  
Yonglong Yu ◽  
Long Xu ◽  
Xiaohui Liu
Keyword(s):  
Kalman Filtering ◽  
Data Transmission ◽  
Stochastic Systems ◽  
Minimum Mean Square Error ◽  
Multiplicative Noises ◽  
Augmented System ◽  
Analysis Technique ◽  
State Augmentation ◽  
Innovation Analysis ◽  
Filtering Problem

This paper is concerned with the optimal Kalman filtering problem for a class of discrete stochastic systems with multiplicative noises and random two-step sensor delays. Three Bernoulli distributed random variables with known conditional probabilities are introduced to characterize the phenomena of the random two-step sensor delays which may happen during the data transmission. By using the state augmentation approach and innovation analysis technique, an optimal Kalman filter is constructed for the augmented system in the sense of the minimum mean square error (MMSE). Subsequently, the optimal Kalman filtering is derived for corresponding augmented system in initial instants. Finally, a simulation example is provided to demonstrate the feasibility and effectiveness of the proposed filtering method.

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