Hierarchical Fusion Estimation With Feedback for Clustered Sensor Networks Subject to Leader and Subordinate Sensors

• Published in: IEEE transactions on circuits and systems. II, Express briefs p. 1
• Main Authors: Cao, Xinyue, Zhao, Ling, Xia, Yuanqing, Yang, Hongjiu
• Format: Journal Article
• Language: English
• Published: IEEE 2025
• Subjects: Accuracy; clustered sensor networks; Covariance matrices; Estimation; Estimation error; feedback; Fusion estimation; hierarchical fusion; Linear systems; Noise; Noise measurement; Symmetric matrices; Target tracking; Training
• DOI: 10.1109/TCSII.2025.3598216
• ISSN: 1549-7747

In this paper, hierarchical fusion estimation with feedback is researched in clustered sensor networks with leader and subordinate sensors. A local estimator is designed to obtain local estimates using feedback fusion estimates in each sensor. A two-layer fusion estimator is developed to achieve fusion estimates for improving estimation accuracy in each leader sensor. The first layer fusion estimator is proposed combining local estimates within the same cluster based on both current and past local estimation accuracy under inaccurate noise covariance matrices. The second layer fusion estimator is designed by fusing the first layer fusion estimates from all leader sensors. Validity of the hierarchical fusion estimation with feedback is shown based on a maneuvering target tracking system.