The Distributed and Centralized Fusion Filtering Problems of Tessarine Signals from Multi-Sensor Randomly Delayed and Missing Observations under T k -Properness Conditions

José D. Jiménez-López, Rosa M. Fernández-Alcalá, Jesús Navarro-Moreno and Juan C. Ruiz-Molina
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José D. Jiménez-López: Department of Statistics and Operations Research, University of Jaén, Paraje Las Lagunillas, 23071 Jaén, Spain
Rosa M. Fernández-Alcalá: Department of Statistics and Operations Research, University of Jaén, Paraje Las Lagunillas, 23071 Jaén, Spain
Jesús Navarro-Moreno: Department of Statistics and Operations Research, University of Jaén, Paraje Las Lagunillas, 23071 Jaén, Spain
Juan C. Ruiz-Molina: Department of Statistics and Operations Research, University of Jaén, Paraje Las Lagunillas, 23071 Jaén, Spain

Mathematics, 2021, vol. 9, issue 22, 1-34

Abstract: This paper addresses the fusion estimation problem in tessarine systems with multi-sensor observations affected by mixed uncertainties when under T k -properness conditions. Observations from each sensor can be updated, delayed, or contain only noise, and a correlation is assumed between the state and the observation noises. Recursive algorithms for the optimal local linear filter at each sensor as well as both centralized and distributed linear fusion estimators are derived using an innovation approach. The T k -properness assumption implies a reduction in the dimension of the augmented system, which yields computational savings in the previously mentioned algorithms compared to their counterparts, which are derived from real or widely linear processing. A numerical simulation example illustrates the obtained theoretical results and allows us to visualize, among other aspects, the insignificant difference in the accuracy of both fusion filters, which means that the distributed filter, although suboptimal, is preferable in practice as it implies a lower computational cost.

Keywords: centralized fusion estimation; delayed observations; distributed fusion estimation; multi-sensor systems; tessarine signal processing; T k -properness; uncertain observations (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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