Centralized Fusion Estimators for Multisensor Systems With Random Sensor Delays, Multiple Packet Dropouts and Uncertain Observations

• Published in: IEEE sensors journal Vol. 13; no. 4; pp. 1228 - 1235
• Main Authors: Ma, Jing, Sun, Shuli
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2013; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Centralized fusion estimator; Computational efficiency; Delay; Dropouts; Estimation; Estimators; Filtering algorithms; Maximum likelihood detection; multisensor; Noise; Optimization; packet dropout; random delay; Sensors; Steady-state; Stochastic systems; uncertain observation; Uncertainty
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2012.2227995

For linear discrete-time stochastic systems measured by multiple sensors, where different sensors are subject to mixed uncertainties of random delays, packet dropouts and/or uncertain observations, the centralized fusion linear optimal estimators in the linear minimum variance sense are presented via the innovation analysis approach, which is a general and useful tool to find the optimal linear estimate. The stability of the proposed estimators is analyzed. A sufficient condition for the existence of the centralized fusion steady-state estimators is given. For a single sensor case, the proposed estimators have the simpler forms and the lower computational cost compared to the existing literature, since a lower dimension parameterized system is constructed and the colored noise is avoided. A simulation example verifies the effectiveness of the proposed estimators.