Distributed fusion filtering for multi-sensor nonlinear networked systems with multiple fading measurements via stochastic communication protocol

• Published in: Information fusion Vol. 112; p. 102543
• Main Authors: Hu, Jun, Hu, Zhibin, Caballero-Águila, Raquel, Yi, Xiaojian
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2024
• Subjects: Distributed fusion filtering; Inverse covariance intersection fusion; Multiple fading measurements; Stochastic communication protocol; Time-varying nonlinear delayed systems; Stochastic communication protocol; Distributed fusion filtering; Time-varying nonlinear delayed systems; Inverse covariance intersection fusion; Multiple fading measurements
• ISSN: 1566-2535; 1872-6305
• DOI: 10.1016/j.inffus.2024.102543

This paper studies the distributed fusion filtering (DFF) issue for a class of nonlinear delayed multi-sensor networked systems (MSNSs) subject to multiple fading measurements (MFMs) under stochastic communication protocol (SCP). The phenomenon of MFMs occurs randomly in the network communication channels and is characterized by a diagonal matrix with certain statistical information. In order to decrease the overload of communication network and save network resources, the SCP that can regulate the information transmission between sensors and estimators is adopted. The primary aim of the tackled problem is to develop the DFF method for nonlinear delayed MSNSs in the presence of MFMs and SCP based on the inverse covariance intersection fusion rule. In addition, the local upper bound (UB) of the filtering error covariance (FEC) is derived and minimized by means of suitably designing the local filter gain. Moreover, the boundedness analysis regarding the local UB is proposed with corresponding theoretical proof. Finally, two simulation examples with comparative illustrations are given to display the usefulness and feasibility of the derived theoretical results. •A new DFF algorithm is developed for nonlinear delayed MSNSs with MFMs and SCP.•The minimized upper bound (UB) concerning the FEC is presented by selecting local filter (LF) gain.•A sufficient condition is given to ensure that the UB on the FEC is bounded uniformly.